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IMH, Duke-NUS and Neeuro Pilot Home-Based Brain-Training Game to Help Children with ADHD

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Nov 06, 2019

• Researchers at IMH, Duke-NUS and A*STAR have developed an advanced brain-computer interface technology that harnesses machine learning to personalise brain-training for children with ADHD.
• Partnering local tech start-up, Neeuro, the researchers are rolling out a pilot home-based intervention programme for children with ADHD undergoing treatment at IMH. The take-home kit comprises a wireless headband and a Samsung tablet with the pre-loaded game.
• Extensive clinical testing through a large-scale randomised clinical trial of the game-based brain-training programme found improvements in the attention span of children with ADHD.

Singapore, 6 November 2019 --( ASIA TODAY )-- A first-of-its-kind personalised, interactive brain-training game will soon be helping children with Attention Deficit Hyperactivity Disorder (ADHD) improve their attention span. The unique selling point of this technology is that children with ADHD can participate in this programme from home. A pilot run for the home-based programme will be launched for 20 children, aged 6-12 years, who are currently receiving treatment for ADHD at the Institute of Mental Health (IMH).

The game, called CogoLand1, was developed through a decade’s worth of extensive research, utilising Brain-Computer Interface (BCI) technology that incorporates machine-learning algorithms to personalise attention training, with the hope of complementing mainstay ADHD treatment. The use of CogoLand to complement ADHD treatment is the result of a collaboration between IMH, Duke-NUS Medical School and A*STAR’s Institute for Infocomm Research (I2R). Neeuro Pte Ltd, a local tech startup and spinoff from A*STAR, is the current sole licensee of the technology.

This non-invasive ADHD intervention programme was the subject of a large scale randomised clinical trial funded by the National Medical Research Council, involving 172 children with ADHD in Singapore.2 Associate Professor Lee Tih Shih, from Duke-NUS’ Neuroscience and Behavioural Disorders programme and Principal Investigator of the large scale clinical trial, commented: “Our patented, personalised intervention using advanced BCI technology has shown very promising and robust results, and we hope it can benefit many children with ADHD in the future.”

Furthermore, Functional Magnetic Resonance Imaging (fMRI) scans of a subset of the children, led by Associate Professor Juan Helen Zhou, also from Duke-NUS, showed positive post-training effects observed in brain areas associated with attention and task-orientation.3 The patented technology was summarised by Professor Guan Cuntai, technical lead of the system and scientific advisor to Neeuro: “Our technology can accurately quantify a person’s attention level in real-time using a machine learning algorithm and, from there, develop a unique patented personalised training programme using a feed-forward concept for cognitive training. Further improvements have been made in recent iterations by capitalising on the latest deep learning approaches with our large dataset.” Professor Guan was also the Principal Scientist who led the BCI research when he was part of A*STAR’s I2R.

Dr Lim Choon Guan, Deputy Chief of the Department of Developmental Psychiatry at IMH said: “While medication and behavioural therapy are effective in treating symptoms of ADHD in children, some parents are also keen to explore other approaches that can help their children to improve their concentration. After a decade of collaborative work, our team is very excited to pilot this home-based brain-training game which parents can use to help their children regulate themselves.” The home-based programme will see the 20 children each receive a take-home kit that includes Neeuro’s brainwave-reading SenzeBand and a Samsung tablet with the preloaded CogoLand game, which they will use following a prescribed regimen for the duration of the programme. This approach is intended to be a complement and/or supplement to conventional ADHD treatment.

According to Dr. Alvin Chan, CEO and Co-Founder of Neeuro, “At Neeuro, our aim is to utilise technology to enable positive change in the neurological agility and fitness of our users. We are privileged to be working with institutions such as IMH, Duke-NUS and A*STAR, in conjunction with our hardware partner Samsung, to explore the use of cutting-edge technology in order to achieve this aim. It is our hope that this trial paves the way to enable the progressive development of new complementary options that will bring about positive outcomes for the millions of children afflicted with ADHD globally, especially those in Singapore.”

Mr Philip Lim, CEO of A*STAR’s innovation and enterprise office A*ccelerate, said: “It is always fulfilling when homegrown technologies are translated into meaningful outcomes. We are proud to be a part of Neeuro’s journey, and A*STAR will continue supporting entrepreneurial companies like them to grow and innovate.”

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1 See Annex A for more information on CogoLand.

2 Lim, C., Poh, X., Fung, S., Guan, C., Bautista, D., & Cheung, Y. et al. (2019). A randomized controlled trial of a brain-computer interface based attention training program for ADHD. PLOS ONE, 14(5), e0216225. DOI: 10.1371/journal.pone.0216225

3 Qian, X., Loo, B., Castellanos, F., Liu, S., Koh, H., & Poh, X. et al. (2018). Brain-computer-interface-based intervention re-normalizes brain functional network topology in children with attention deficit/hyperactivity disorder. Translational Psychiatry, 8(1). DOI: 10.1038/s41398-018-0213-8

Note: The research study was funded by grants from the National Medical Research Council (NMRC) and National Healthcare Group (NHG). The research team also acknowledges the support received from the Ministry of Education, Singapore.

About Neeuro
Its core technology, NeeuroOS, is a platform ecosystem that empowers health care professionals, researchers and third party developers with an Artificial Intelligence (AI) driven platform with the ability to analyse the brain signals of users; measuring mental states including but not limited to attention, relaxation, mental workload and fatigue. Neeuro’s holistic platform, coupled with its other offerings, reveal numerous potential avenues to explore complementary mental wellness options for ADHD children, patients with stroke, cognitive rehabilitation and many other neurological issues.

For more information, please visit https://www.neeuro.com.
Comms Contacts
Kelly Choo
Neeuro Pte. Ltd.
Tel: +65 6397 5153
Email: contact@neeuro.com

Fiona Foo
Institute of Mental Health
Tel: +65 6389 2868 / +65 8123 8805
Email: Fiona_wy_foo@imh.com.sg

Federico Graciano
Duke-NUS Communications
Tel: +65 6601 3272
Email: f.graciano@duke-nus.edu.sg

Gladys Chung
A*STAR Corporate Communications
Tel: +65 6826 6348
Email: Gladys_chung@hq.a-star.edu.sg

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Collaboration / Partnership
Medicine & Health Care
Science Research
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Google previews site for sharing machine learning experiments

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Google has unveiled TensorBoard.dev, an online platform where data scientists, researchers, machine learning practitioners, and software developers can share machine learning experiments and collaborate on machine learning projects. 

Now in a beta release stage, TensorBoard.dev lets users upload machine learning experiments for sharing with anyone. The platform leverages the TensorBoard visualization toolkit, which works with Google’s TensorFlow library for machine learning and deep learning.

To read this article in full, please click here


          

Google Cloud launches TensorFlow Enterprise

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Google Cloud has introduced TensorFlow Enterprise, a cloud-based TensorFlow machine learning service that includes enterprise-grade support and managed services.

Based on Google’s popular, open source TensorFlow machine learning library, TensorFlow Enterprise is positioned to help machine learning researchers accelerate the creation of machine learning and deep learning models and ensure the reliability of AI applications. Workloads in Google Cloud can be scaled and compatibility-tested.

To read this article in full, please click here


          

KDnuggets™ News 19:n42, Nov 6: 5 Statistical Traps Data Scientists Should Avoid; 10 Free Must-Read Books on AI

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Learn about statistical fallacies Data Scientists should avoid; New and quite amazing Deep Learning capabilities FB has been quietly open-sourcing; Top Machine Learning tools for Developers; How to build a Neural Network from scratch and more.
          

Facebook Has Been Quietly Open Sourcing Some Amazing Deep Learning Capabilities for PyTorch

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The new release of PyTorch includes some impressive open source projects for deep learning researchers and developers.
          

Naïo Technologies récompensé par le salon Agritechnica

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Le robot Dino de l'entreprise toulousaine Naïo Technologies a été médaillé d'argent au palmarès de l'Innovation 2019 dévoilé par le Agritechnica, à Hanovre. L'outil, destiné au désherbage des salades, combine plusieurs technologies pour désherber à la fois entre les rangs et entre les plants.
« C'est un système de captation des cultures sous le robot, basé sur des technologies de deep learning. La machine est capable, grâce à un apprentissage et un entraînement préalables, de reconnaître et distinguer des (...)

- En bref /
          

Senior AI/Deep Learning Software Engineer - St Josephs Hospital and Medical Center - Phoenix, AZ

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Ability to align business needs to development and machine learning or artificial intelligence solutions. Experience in natural language understanding, computer…
From Dignity Health - Tue, 27 Nov 2018 03:06:49 GMT - View all Phoenix, AZ jobs
          

Noninvasive Histopathological Imaging of Brain and Prostate Cancer

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Being the routine clinical practice for most cancer types, assessing tumor histopathology is critical for cancer diagnosis and prognosis. Histological reviews by clinical pathologist based on the tissue from biopsy or surgical resection remain the only definitive diagnosis of tumor pathologies. However, biopsy or surgical resection is invasive with potential adverse side-effects, making it urgent to develop noninvasive imaging techniques for assessing tumor histopathology. Diffusion MRI was proved to be sensitive to cancer detection in several types of cancer. Yet, current diffusion MRI methods are not specific enough to assess tumor histopathology, especially for cancers like glioblastoma (GBM) and prostate cancer, most with complicated tumor micro-environment. To address this challenge, we employ a novel Diffusion Histology Imaging (DHI) approach, combining diffusion basis spectrum imaging (DBSI) and machine learning/deep learning, to accurately and non-invasively assess tumor histopathology. We apply DHI in imaging patients with GBM to reveal potential viable tumor and necrosis regions that current clinical imaging gold is not able to detect. For validation, we examined twenty surgical resection specimens from thirteen GBM patients and demonstrated that DBSI-derived restricted isotropic diffusion fraction significantly correlated with GBM tumor cellularity. The results further indicated that DHI predicted high cellularity tumor, tumor necrosis, and tumor infiltration with accuracy rate of respectively 91.9%, 93.7%, and 87.8%. It was suggested that DHI might serve as a favorable alternative to current neuroimaging techniques in guiding biopsy or surgery as well as monitoring therapeutic response in the treatment of glioblastomas. Similarly, we applied DHI on prostatectomy specimen and prostate cancer patients, and it was highly accurate not only in detecting prostate cancer from other benign prostatic histology or structures, but also in classifying various prostate cancer grades (grade 1: 88%; grade 2: 94%; grade 3: 92%; grade 4: 88%; grade 5: 95%). We demonstrated that through evaluating and profiling various histopathological structures in prostate cancer, DHI could increase accuracy of tumor detection, staging and grading.


          

PyCoder’s Weekly: Issue #393 (Nov. 5, 2019)

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#393 – NOVEMBER 5, 2019
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The PyCoder’s Weekly Logo


Python Adopts a 12-Month Release Cycle (PEP 602)

The CPython team moves to a consistent annual release schedule. More info here in PEP 602.
LWN.NET

Build a Mobile App With the Kivy Python Framework

Learn how to build a mobile application with Python and the Kivy GUI framework. You’ll discover how to develop an application that can run on your desktop as well as your phone. Then, you’ll package your app for iOS, Android, Windows, and macOS.
REAL PYTHON

Become a Python Guru With PyCharm

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PyCharm is the Python IDE for Professional Developers by JetBrains providing a complete set of tools for productive Python, Web and scientific development. Be more productive and save time while PyCharm takes care of the routine →
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The 2019 Python Developer Survey

“[We] aim to identify how the Python development world looks today and how it compares to the last two years. The results of the survey will serve as a major source of knowledge about the current state of the Python community and how it is changing over the years, so we encourage you to participate and make an invaluable contribution to this community resource. The survey takes approximately 10 minutes to complete.”
PSF BLOG

You Don’t Have to Migrate to Python 3

“Python 3 is great! But not every Python 2 project has to be migrated. There are different ways how you can prepare for the upcoming Python 2 End of Life.”
SEBASTIAN WITOWSKI

Why You Should Use python -m pip

Arguments for why you should always use python -m pip over pip/pip3 to control exactly which Python environment is used.
BRETT CANNON

Thank You, Guido

“After six and a half years, Guido van Rossum, the creator of Python, is leaving Dropbox and heading into retirement.”
DROPBOX.COM

Python Jobs

Django Full Stack Web Developer (Austin, TX, USA)

Zeitcode

Full Stack Developer (Toronto, ON, Canada)

Beanfield Metroconnect

Full Stack Software Developer (Remote)

Cybercoders

Full-Stack Python/Django Developer (Remote)

Kimetrica, LLC

Sr. Python Data Engineer (Remote)

TEEMA Solutions Goup

More Python Jobs >>>

Articles & Tutorials

Cool New Features in Python 3.8

What does Python 3.8 bring to the table? Learn about some of the biggest changes and see you how you can best make use of them.
REAL PYTHON video

Practical Log Viewers With Sanic and Elasticsearch

How to view log output from Docker containers in an automated CI/CD system in your GitHub pull requests, using Elasticsearch and a Python REST API built with Sanic.
CRISTIAN MEDINA • Shared by Cristian Medina

Python Developers Are in Demand on Vettery

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Vettery is an online hiring marketplace that’s changing the way people hire and get hired. Ready for a bold career move? Make a free profile, name your salary, and connect with hiring managers from top employers today →
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Traffic Sign Classification With Keras and Deep Learning

How to train your own traffic sign classifier/recognizer capable of obtaining over 95% accuracy using Keras and Deep Learning.
ADRIAN ROSEBROCK

Python REST APIs With Flask, Connexion, and SQLAlchemy

In Part 4 of this series, you’ll learn how to create a Single-Page Application (SPA) to interface with the REST API backend that you built in Part 3. Your SPA will use HTML, CSS, and JavaScript to present this REST API to a user as a browser-based web application.
REAL PYTHON

How We Spotted and Fixed a Performance Degradation in Our Python Code

A post-mortem of how Omer’s team tracked down and fixed a performance regression introduced by a switch from Celery to RQ.
OMER LACHISH

Python: Better Typed Than You Think

MyPy assisted error handling, exception mechanisms in other languages, fun with pattern matching and type variance.
DMITRII GERASIMOV

Finding Definitions From a Source File and a Line Number in Python

Considering a filename and a line number, can you tell which function, method or class a line of code belongs to?
JULIEN DANJOU

Visual Studio Online: Web-Based IDE & Collaborative Code Editor

Microsoft announced Visual Studio Online, an online IDE and cloud-based development environment based on VS Code.
MICROSOFT.COM

Serving Static Files From Flask With WhiteNoise and Amazon CloudFront

This tutorial shows how to manage static files with Flask, WhiteNoise, and Amazon CloudFront.
MICHAEL HERMAN

Easily Build Beautiful Video Experiences Into Your Python App

Mux Video is an API-first platform, powered by data and designed by video experts. Test it out to build video for your Python app that streams beautifully, everywhere.
MUX sponsor

Projects & Code

Events

Python Miami

November 9 to November 10, 2019
PYTHONDEVELOPERSMIAMI.COM

PiterPy Meetup

November 12, 2019
PITERPY.COM


Happy Pythoning!
This was PyCoder’s Weekly Issue #393.
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A.M. Best: Insurance Has an Imperative to Address AI and the “Art of the Possible”

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A.M. Best recently hosted a webinar on the Insurance AI Imperative, featuring expert speakers and sponsored by Cognizant. Host Jon Weber of A.M. Best framed the discussion as an opportunity for some insurers to get ahead of the pack, while others could fall behind. The panelists were Jennifer Herz and Mike Clifton of Cognizant, a multinational IT company. Mike Clifton kicked things off in response to a question from Weber regarding whether AI is more “sizzle than steak” by explaining that AI is a vast area of technology. “Being an early adopter fits depending on your business profile and business acumen,” he said. “If you look at the spectrum of AI, there’s people who think of AI as purely just the ability for a machine to make a decision.” However, according to Clifton, the excitement in the industry is coming from the maturity of the technology - machine models and deep learning. Ultimately, he said, modern insurers must “digitally pivot and AI should be part of that strategy.” For the timeline of a fully mature AI timeline, Clifton again emphasized that it depends on the company’s business model and efficiency. Herz added that, “it’s a moving target, what we think is fully mature today, likely 24 months from now is going to feel completely different,” but that deriving the most benefit from AI initiatives through a carrier's business priorities is the key. Weber then shifted the discussion to the “disruptions” that AI is due to create, other than competition from insurtechs and start-ups, which has been much reported on throughout the industry. For Clifton, it all comes down to the insurtechs providing focus. “They give us the ability to laser in on a particular set of problems, like claims or catastrophe management,” he said. “That helps because it makes the value of that interaction well-known. The disruption elements are still occurring from an insurance industry perspective in that you’re seeing a lot of the easier risk appetites of the products being looked at as very targeted spaces to automate and use AI.” Clifton cited warranty coverage and rental coverage as examples. With respect to AI trends within the insurance industry at large, Herz said that incorporating different technology skill sets (especially among millennial workers) is something she hears frequently from the companies she works with as talent leaves the industry and new talent enters. Further, she noted that there is an emphasis on “shoring up the data infrastructure of companies” so that they can integrate data analysis, third party data and, thus, AI technology. These efforts marry with the “evolution of the customer experience” so that as technological innovation continuously accelerates, so do the needs of the customer. This is what Cognizant refers to as the “art of the possible” in adding with AI to the entire value stream of insurance.           Making the case that a “wait and see” approach is insufficient, Herz said that it’s all about where you want to drive growth. “Most companies can’t invest everywhere and have to pick where are the places they can get the most value. It’s a matter of how do you test and learn quickly and then how do you scale so that you can continue to drive benefit as you move through the [AI] maturity curve,” she explained. At the conclusion of the webinar, Weber invited the panelists to voice their essential takeaways from the presentation. For Clifton, it was all about the core of machine learning and models in actuarial science transferring to the frontlines. “AI will be foundational to how we implement insurance in the future, especially property and casualty,” he said. Herz added to the point, saying that she wanted registrants to remember that “understanding where you are and what your business strategy is and how the AI ecosystem can enable that strategy” will help provide focus.   This A.M. Best webinar is available on demand here.   Image Credit: A.M. Best via Twitter  
          

Principal Technical Product Manager - Telecom OSS/BSS Applications and Services - Amazon.com Services, Inc. - Bellevue, WA

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Machine Learning and Deep Learning applicability to Telecom services. Strong understanding of business flows and integrated up stream & downstream applications.
From Amazon.com - Fri, 09 Aug 2019 07:52:12 GMT - View all Bellevue, WA jobs
          

Health Data Lead

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Overview Are you ready to join an organization where you can make an extraordinary impact every day? Imagine all Americans enjoying ideal cardiovascular health free of heart disease and stroke. At the American Heart Association and American Stroke Association, we get to work toward that goal every day. Is it easy? No. Is it worthwhile? Absolutely. This is satisfying and challenging work that makes a real difference in people's lives. We are where you can achieve professional growth with personal fulfillment. We are where you can connect people to making a lifesaving impact. We are where you can partner with individuals, schools, lawmakers, healthcare providers and others to ensure everyone has access to healthier lifestyle choices and proper healthcare. The American Heart Association is where you can make an extraordinary impact. Responsibilities The Lead Health Data Science Assets is a new exciting role that offers a unique opportunity to lead data strategy across the organization! This role will work with our Emerging Strategies and Ventures Team and serve as a critical liaison between Emerging Health and Business strategies, the AHA's Mission Aligned Business and Health Solutions teams and other business segments. This role is vital to American Heart Association's efforts that bring to bear healthcare and science data as a core asset and growth driver, crafting an outstanding organization and capability that will support quantifiable outcomes, enable identification of new product opportunities and deliver unrivaled data partnerships that fuel creativity. We are looking for someone who is highly motivated, who is an expert data innovator, and who can share tangible results from their strategies, leadership actions. We also need someone who has current experience in large growth organizations where data is a core capability for creating outcomes. Essential Job Duties Develop and implement solutions built on a scalable and flexible architecture that will allow AHA to handle and use health data as an enterprise business asset Define and implement standard operating practices for health data collection, ingestion, storage, transformation, distribution, integration, and consumption within AHA's Health solutions portfolio. Lead all aspects of data access and distribution. Lead the design and delivery of Data Business Intelligence AI and automation solutions advisory engagements involving strategy, roadmap and longer-term operating models. Support the delivery of a broad range of data assets and analytics. Identify and demonstrate approaches, appropriate tools and methodologies. Run health data quality and security. Define data standards, policies and procedures ensuring effective and efficient data management across the company. Provide expertise and leadership in the disciplines of data governance, data quality and master data integration and architecture. Establish a data governance framework. Maintain and share data definitions, data integrity, security and classifications. Direct the continued design, build, and operations of our Big Data Platforms and Solutions. Help identify and understand data from internal and external sources for competitive, scenario and performance analyses, and financial modeling to gain insight into new and existing processes and business opportunities. Work with business teams on commercial and non-commercial opportunities. Advise on fair market value data value propositions Actively contribute to proposal development of transformation engagements focused on DataAnalytics AI and automation. Demonstrate thought leadership to advise teams on DataAnalytics, AI and automation strategy and detailed use cases development by industry. Possess deep understanding of trends and strategies for identifying solutions to meet objectives. Monitor technology trends and raise awareness of capabilities and innovations in selected domains of expertise Empower Data Architecture team to create optimized data pipelines, data storage and data transformation. Support the practice with depth of experience and expertise in the following domains: automation, machine learning, deep learning, advanced analytics, data science, data aggregation & visualization Qualifications Bachelors' degree from a globally recognized institution of higher learning is required, with an advanced degree (MS, PhD, equivalent) strongly preferred. 10 years experience in a company known for data innovation and excellence with responsibility for a comparably- sized analytics business 10 years experience in Health data, real world evidence analytics andor health informatics with the capability to design data strategies and source key health data, gain acceptability for methods, and build analyses for benefit-risk justifications, development and other regulatory needs Experience implementing and using cutting edge analytic tools and capabilities, including B2B, B2C and cross-channel integration tools A passion for and experience with big data-driven decision-making processes across business functions Demonstrated ability to work with technical team of product and data engineers, as well as data scientistsPhDs Consistent track record of successfully delivering top and bottom-line results individually and as part of a high-performance team. Outstanding oralwritten communication and presentation skills, especially with respect to clearly communicating complex data-driven topics to both technical and non-technical audiences. Strategic thinker, leadership, communication, people management skills and innovator with ability to work across segments to support tactical planning and deliver on the objectives of organization. Knowledge of Technology and Healthcare, Life sciences and Health-tech Industry trends Creative, collaborative thinker with an ability to learn new things, assess problems and identify proactive solutions quickly Self-starter, comfortable leading change and getting things done. Travel is required (at least 10%), including overnights. Location: Dallas, Texas is preferred. At American Heart Association - American Stroke Association, diversity, inclusion, and equal opportunity applies to both our workforce and the communities we serve as it relates to heart health and stroke prevention. Be sure to follow us on Twitter to see what it is like to work for the American Heart Association and why so many people enjoy #TheAHALife EOE MinoritiesFemalesProtected VeteransPersons with Disabilities Requisition ID 2018-3066 Job Family Group Business Operations Job Category Science & Research Additional Locations US-Anywhere US-Anywhere Location: Charleston,WV
          

Health Data Lead

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Overview Are you ready to join an organization where you can make an extraordinary impact every day? Imagine all Americans enjoying ideal cardiovascular health free of heart disease and stroke. At the American Heart Association and American Stroke Association, we get to work toward that goal every day. Is it easy? No. Is it worthwhile? Absolutely. This is satisfying and challenging work that makes a real difference in people's lives. We are where you can achieve professional growth with personal fulfillment. We are where you can connect people to making a lifesaving impact. We are where you can partner with individuals, schools, lawmakers, healthcare providers and others to ensure everyone has access to healthier lifestyle choices and proper healthcare. The American Heart Association is where you can make an extraordinary impact. Responsibilities The Lead Health Data Science Assets is a new exciting role that offers a unique opportunity to lead data strategy across the organization! This role will work with our Emerging Strategies and Ventures Team and serve as a critical liaison between Emerging Health and Business strategies, the AHA's Mission Aligned Business and Health Solutions teams and other business segments. This role is vital to American Heart Association's efforts that bring to bear healthcare and science data as a core asset and growth driver, crafting an outstanding organization and capability that will support quantifiable outcomes, enable identification of new product opportunities and deliver unrivaled data partnerships that fuel creativity. We are looking for someone who is highly motivated, who is an expert data innovator, and who can share tangible results from their strategies, leadership actions. We also need someone who has current experience in large growth organizations where data is a core capability for creating outcomes. Essential Job Duties Develop and implement solutions built on a scalable and flexible architecture that will allow AHA to handle and use health data as an enterprise business asset Define and implement standard operating practices for health data collection, ingestion, storage, transformation, distribution, integration, and consumption within AHA's Health solutions portfolio. Lead all aspects of data access and distribution. Lead the design and delivery of Data Business Intelligence AI and automation solutions advisory engagements involving strategy, roadmap and longer-term operating models. Support the delivery of a broad range of data assets and analytics. Identify and demonstrate approaches, appropriate tools and methodologies. Run health data quality and security. Define data standards, policies and procedures ensuring effective and efficient data management across the company. Provide expertise and leadership in the disciplines of data governance, data quality and master data integration and architecture. Establish a data governance framework. Maintain and share data definitions, data integrity, security and classifications. Direct the continued design, build, and operations of our Big Data Platforms and Solutions. Help identify and understand data from internal and external sources for competitive, scenario and performance analyses, and financial modeling to gain insight into new and existing processes and business opportunities. Work with business teams on commercial and non-commercial opportunities. Advise on fair market value data value propositions Actively contribute to proposal development of transformation engagements focused on DataAnalytics AI and automation. Demonstrate thought leadership to advise teams on DataAnalytics, AI and automation strategy and detailed use cases development by industry. Possess deep understanding of trends and strategies for identifying solutions to meet objectives. Monitor technology trends and raise awareness of capabilities and innovations in selected domains of expertise Empower Data Architecture team to create optimized data pipelines, data storage and data transformation. Support the practice with depth of experience and expertise in the following domains: automation, machine learning, deep learning, advanced analytics, data science, data aggregation & visualization Qualifications Bachelors' degree from a globally recognized institution of higher learning is required, with an advanced degree (MS, PhD, equivalent) strongly preferred. 10 years experience in a company known for data innovation and excellence with responsibility for a comparably- sized analytics business 10 years experience in Health data, real world evidence analytics andor health informatics with the capability to design data strategies and source key health data, gain acceptability for methods, and build analyses for benefit-risk justifications, development and other regulatory needs Experience implementing and using cutting edge analytic tools and capabilities, including B2B, B2C and cross-channel integration tools A passion for and experience with big data-driven decision-making processes across business functions Demonstrated ability to work with technical team of product and data engineers, as well as data scientistsPhDs Consistent track record of successfully delivering top and bottom-line results individually and as part of a high-performance team. Outstanding oralwritten communication and presentation skills, especially with respect to clearly communicating complex data-driven topics to both technical and non-technical audiences. Strategic thinker, leadership, communication, people management skills and innovator with ability to work across segments to support tactical planning and deliver on the objectives of organization. Knowledge of Technology and Healthcare, Life sciences and Health-tech Industry trends Creative, collaborative thinker with an ability to learn new things, assess problems and identify proactive solutions quickly Self-starter, comfortable leading change and getting things done. Travel is required (at least 10%), including overnights. Location: Dallas, Texas is preferred. At American Heart Association - American Stroke Association, diversity, inclusion, and equal opportunity applies to both our workforce and the communities we serve as it relates to heart health and stroke prevention. Be sure to follow us on Twitter to see what it is like to work for the American Heart Association and why so many people enjoy #TheAHALife EOE MinoritiesFemalesProtected VeteransPersons with Disabilities Requisition ID 2018-3066 Job Family Group Business Operations Job Category Science & Research Additional Locations US-Anywhere US-Anywhere Location: El Paso,TX
          

SICU RN

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Supplemental Health Care is a nationally recognized healthcare staffing provider partnering with a hospital in the South Coast area of Massachusetts to provide an SICU RN. Facility Details: The facility is a 293-bed hospital serving the community of New Bedford, MA. The facility offer a wide range of medical and surgical services and specializes in neurosurgery, cardiology, and general surgery. In the last decade, the facility has invested significantly in building new and upgrading its facilities: new Emergency Department with private treatment bays, upgraded Operating Rooms and Endoscopy Departments, and an upgrade Inpatient Pharmacy Department. RNs here can enjoy easy access to the world-famous beaches of Rhode Island and Cape Cod. Job Description: The Surgical Intensive Care Unit RN will provide care for patients in critical condition recovering from surgery or trauma surgery. The Surgical ICU Registered Nurse will work in a highly challenging environment requiring deep knowledge and strong experience in surgical critical care and trauma care. The Surgical Intensive Care unit will assign the RN 1-2 patients to manage in a given shift, but may increase the number to 3-4 as the situation requires. This SICU position is for any RN with a propensity for high challenge, deep learning and great skill development. Job Details: Location: New Bedford, MA Type: All positions start as 13-week Contracts Shift: Nights (7P-7A) Hours: 36-40/Week Start: ASAP Compensation: $42-45 per hour Benefits: Health, Dental, Vision, 401K, FSA, HSA, PTO About Us: Founded in 1984, Supplemental Health Care has grown into one of the largest staffing companies in Healthcare. With a proven track record, we remain a trusted and reliable partner for our clients and talents across the country. Working with Supplemental Health Care, you will have dedicated resources and a team to support and ensure success in your career endeavors. For Immediate Consideration: Please contact Toan Huynh, Staffing Manager, at 339-298-7515.
          

Python, Hadoop, and Machine Learning Software Engineer

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SunIRef:it Python, Hadoop, and Machine Learning Software Engineer JP Morgan Chase 21,658 reviews - Wilmington, DE 19803 JP Morgan Chase 21,658 reviews Read what people are saying about working here. As a member of our Software Engineering Group we look first and foremost for people who are passionate around solving business problems through innovation & engineering practices. You will be required to apply your depth of knowledge and expertise to all aspects of the software development lifecycle, as well as partner continuously with your many stakeholders on a daily basis to stay focused on common goals. We embrace a culture of experimentation and constantly strive for improvement and learning. You'll work in a collaborative, trusting, thought-provoking environmentone that encourages diversity of thought and creative solutions that are in the best interests of our customers globally. This role requires a wide variety of strengths and capabilities, including: BS/BA degree or equivalent experience Advanced knowledge of application, data and infrastructure architecture disciplines Understanding of architecture and design across all systems Working proficiency in developmental toolsets Knowledge of industry wide technology trends and best practices Ability to work in large, collaborative teams to achieve organizational goals, and passionate about building an innovative culture Proficiency in one or more modern programming languages Python and Hadoop Understanding of software skills such as business analysis, development, maintenance and software improvement Experience with Machine Learning, Deep Learning, Data Mining, and/or Statistical Analysis tools. Strong hands-on experience with developing and deploying machine learning based models, statistical models, data mining, and business rules. Background on basic machine learning techniques including supervised, unsupervised, reinforcement and deep learning. Experience with machine learning tools such as Scikit Learn, Pandas, TensorFlow, SparkML, SAS, R, H20, Keras, Caf, Theano, etc. At least 5 years hands-on experience with various programing models such as Spring, Java, Python, or C/C++. Our Consumer & Community Banking Group depends on innovators like you to serve nearly 66 million consumers and over 4 million small businesses, municipalities and non-profits. You'll support the delivery of award winning tools and services that cover everything from personal and small business banking as well as lending, mortgages, credit cards, payments, auto finance and investment advice. This group is also focused on developing and delivering cutting edged mobile applications, digital experiences and next generation banking technology solutions to better serve our clients and customers. When you work at JPMorgan Chase & Co., you're not just working at a global financial institution. You're an integral part of one of the world's biggest tech organizations. In our global technology centers, our team of 50,000 technologists design, build and deploy everything from enterprise technology initiatives to big data and mobile solutions, as well as innovations in electronic payments, cybersecurity, machine learning, and cloud development. Our $11B annual investment in technology enables us to hire people to create innovative solutions that are transforming the financial services industry. At JPMorgan Chase & Co. we value the unique skills of every employee, and we're building a technology organization that thrives on diversity. We encourage professional growth and career development, and offer competitive benefits and compensation. If you're looking to build your career as part of a global technology team tackling big challenges that impact the lives of people and companies all around the world, we want to meet you. JP Morgan Chase - Just posted report job - original job
          

Health Data Lead

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Overview Are you ready to join an organization where you can make an extraordinary impact every day? Imagine all Americans enjoying ideal cardiovascular health free of heart disease and stroke. At the American Heart Association and American Stroke Association, we get to work toward that goal every day. Is it easy? No. Is it worthwhile? Absolutely. This is satisfying and challenging work that makes a real difference in people's lives. We are where you can achieve professional growth with personal fulfillment. We are where you can connect people to making a lifesaving impact. We are where you can partner with individuals, schools, lawmakers, healthcare providers and others to ensure everyone has access to healthier lifestyle choices and proper healthcare. The American Heart Association is where you can make an extraordinary impact. Responsibilities The Lead Health Data Science Assets is a new exciting role that offers a unique opportunity to lead data strategy across the organization! This role will work with our Emerging Strategies and Ventures Team and serve as a critical liaison between Emerging Health and Business strategies, the AHA's Mission Aligned Business and Health Solutions teams and other business segments. This role is vital to American Heart Association's efforts that bring to bear healthcare and science data as a core asset and growth driver, crafting an outstanding organization and capability that will support quantifiable outcomes, enable identification of new product opportunities and deliver unrivaled data partnerships that fuel creativity. We are looking for someone who is highly motivated, who is an expert data innovator, and who can share tangible results from their strategies, leadership actions. We also need someone who has current experience in large growth organizations where data is a core capability for creating outcomes. Essential Job Duties Develop and implement solutions built on a scalable and flexible architecture that will allow AHA to handle and use health data as an enterprise business asset Define and implement standard operating practices for health data collection, ingestion, storage, transformation, distribution, integration, and consumption within AHA's Health solutions portfolio. Lead all aspects of data access and distribution. Lead the design and delivery of Data Business Intelligence AI and automation solutions advisory engagements involving strategy, roadmap and longer-term operating models. Support the delivery of a broad range of data assets and analytics. Identify and demonstrate approaches, appropriate tools and methodologies. Run health data quality and security. Define data standards, policies and procedures ensuring effective and efficient data management across the company. Provide expertise and leadership in the disciplines of data governance, data quality and master data integration and architecture. Establish a data governance framework. Maintain and share data definitions, data integrity, security and classifications. Direct the continued design, build, and operations of our Big Data Platforms and Solutions. Help identify and understand data from internal and external sources for competitive, scenario and performance analyses, and financial modeling to gain insight into new and existing processes and business opportunities. Work with business teams on commercial and non-commercial opportunities. Advise on fair market value data value propositions Actively contribute to proposal development of transformation engagements focused on DataAnalytics AI and automation. Demonstrate thought leadership to advise teams on DataAnalytics, AI and automation strategy and detailed use cases development by industry. Possess deep understanding of trends and strategies for identifying solutions to meet objectives. Monitor technology trends and raise awareness of capabilities and innovations in selected domains of expertise Empower Data Architecture team to create optimized data pipelines, data storage and data transformation. Support the practice with depth of experience and expertise in the following domains: automation, machine learning, deep learning, advanced analytics, data science, data aggregation & visualization Qualifications Bachelors' degree from a globally recognized institution of higher learning is required, with an advanced degree (MS, PhD, equivalent) strongly preferred. 10 years experience in a company known for data innovation and excellence with responsibility for a comparably- sized analytics business 10 years experience in Health data, real world evidence analytics andor health informatics with the capability to design data strategies and source key health data, gain acceptability for methods, and build analyses for benefit-risk justifications, development and other regulatory needs Experience implementing and using cutting edge analytic tools and capabilities, including B2B, B2C and cross-channel integration tools A passion for and experience with big data-driven decision-making processes across business functions Demonstrated ability to work with technical team of product and data engineers, as well as data scientistsPhDs Consistent track record of successfully delivering top and bottom-line results individually and as part of a high-performance team. Outstanding oralwritten communication and presentation skills, especially with respect to clearly communicating complex data-driven topics to both technical and non-technical audiences. Strategic thinker, leadership, communication, people management skills and innovator with ability to work across segments to support tactical planning and deliver on the objectives of organization. Knowledge of Technology and Healthcare, Life sciences and Health-tech Industry trends Creative, collaborative thinker with an ability to learn new things, assess problems and identify proactive solutions quickly Self-starter, comfortable leading change and getting things done. Travel is required (at least 10%), including overnights. Location: Dallas, Texas is preferred. At American Heart Association - American Stroke Association, diversity, inclusion, and equal opportunity applies to both our workforce and the communities we serve as it relates to heart health and stroke prevention. Be sure to follow us on Twitter to see what it is like to work for the American Heart Association and why so many people enjoy #TheAHALife EOE MinoritiesFemalesProtected VeteransPersons with Disabilities Requisition ID 2018-3066 Job Family Group Business Operations Job Category Science & Research Additional Locations US-Anywhere US-Anywhere Location: Birmingham,AL
          

Deep Learning Market Top Key Vendors- IBM Corporation, Intel Corporation, NVIDIA Corporation, Alphabet Inc.

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Zion Market Research published a new 110+ pages industry research “Deep Learning Market: by Application (Speech Recognition, Image Recognition, Data Mining, Drug Discovery, Driver Assistance, and Others), by Components (Hardware and Software), by Architecture (Recurrent Neural Networks (RNN), Convolutional Neural Networks (CNN), Deep Belief Networks (DBN), Deep Stacking Networks (DSN), and Graphical Processing Units (GRU)), and […]
          

Health Data Lead

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Overview Are you ready to join an organization where you can make an extraordinary impact every day? Imagine all Americans enjoying ideal cardiovascular health free of heart disease and stroke. At the American Heart Association and American Stroke Association, we get to work toward that goal every day. Is it easy? No. Is it worthwhile? Absolutely. This is satisfying and challenging work that makes a real difference in people's lives. We are where you can achieve professional growth with personal fulfillment. We are where you can connect people to making a lifesaving impact. We are where you can partner with individuals, schools, lawmakers, healthcare providers and others to ensure everyone has access to healthier lifestyle choices and proper healthcare. The American Heart Association is where you can make an extraordinary impact. Responsibilities The Lead Health Data Science Assets is a new exciting role that offers a unique opportunity to lead data strategy across the organization! This role will work with our Emerging Strategies and Ventures Team and serve as a critical liaison between Emerging Health and Business strategies, the AHA's Mission Aligned Business and Health Solutions teams and other business segments. This role is vital to American Heart Association's efforts that bring to bear healthcare and science data as a core asset and growth driver, crafting an outstanding organization and capability that will support quantifiable outcomes, enable identification of new product opportunities and deliver unrivaled data partnerships that fuel creativity. We are looking for someone who is highly motivated, who is an expert data innovator, and who can share tangible results from their strategies, leadership actions. We also need someone who has current experience in large growth organizations where data is a core capability for creating outcomes. Essential Job Duties Develop and implement solutions built on a scalable and flexible architecture that will allow AHA to handle and use health data as an enterprise business asset Define and implement standard operating practices for health data collection, ingestion, storage, transformation, distribution, integration, and consumption within AHA's Health solutions portfolio. Lead all aspects of data access and distribution. Lead the design and delivery of Data Business Intelligence AI and automation solutions advisory engagements involving strategy, roadmap and longer-term operating models. Support the delivery of a broad range of data assets and analytics. Identify and demonstrate approaches, appropriate tools and methodologies. Run health data quality and security. Define data standards, policies and procedures ensuring effective and efficient data management across the company. Provide expertise and leadership in the disciplines of data governance, data quality and master data integration and architecture. Establish a data governance framework. Maintain and share data definitions, data integrity, security and classifications. Direct the continued design, build, and operations of our Big Data Platforms and Solutions. Help identify and understand data from internal and external sources for competitive, scenario and performance analyses, and financial modeling to gain insight into new and existing processes and business opportunities. Work with business teams on commercial and non-commercial opportunities. Advise on fair market value data value propositions Actively contribute to proposal development of transformation engagements focused on DataAnalytics AI and automation. Demonstrate thought leadership to advise teams on DataAnalytics, AI and automation strategy and detailed use cases development by industry. Possess deep understanding of trends and strategies for identifying solutions to meet objectives. Monitor technology trends and raise awareness of capabilities and innovations in selected domains of expertise Empower Data Architecture team to create optimized data pipelines, data storage and data transformation. Support the practice with depth of experience and expertise in the following domains: automation, machine learning, deep learning, advanced analytics, data science, data aggregation & visualization Qualifications Bachelors' degree from a globally recognized institution of higher learning is required, with an advanced degree (MS, PhD, equivalent) strongly preferred. 10 years experience in a company known for data innovation and excellence with responsibility for a comparably- sized analytics business 10 years experience in Health data, real world evidence analytics andor health informatics with the capability to design data strategies and source key health data, gain acceptability for methods, and build analyses for benefit-risk justifications, development and other regulatory needs Experience implementing and using cutting edge analytic tools and capabilities, including B2B, B2C and cross-channel integration tools A passion for and experience with big data-driven decision-making processes across business functions Demonstrated ability to work with technical team of product and data engineers, as well as data scientistsPhDs Consistent track record of successfully delivering top and bottom-line results individually and as part of a high-performance team. Outstanding oralwritten communication and presentation skills, especially with respect to clearly communicating complex data-driven topics to both technical and non-technical audiences. Strategic thinker, leadership, communication, people management skills and innovator with ability to work across segments to support tactical planning and deliver on the objectives of organization. Knowledge of Technology and Healthcare, Life sciences and Health-tech Industry trends Creative, collaborative thinker with an ability to learn new things, assess problems and identify proactive solutions quickly Self-starter, comfortable leading change and getting things done. Travel is required (at least 10%), including overnights. Location: Dallas, Texas is preferred. At American Heart Association - American Stroke Association, diversity, inclusion, and equal opportunity applies to both our workforce and the communities we serve as it relates to heart health and stroke prevention. Be sure to follow us on Twitter to see what it is like to work for the American Heart Association and why so many people enjoy #TheAHALife EOE MinoritiesFemalesProtected VeteransPersons with Disabilities Requisition ID 2018-3066 Job Family Group Business Operations Job Category Science & Research Additional Locations US-Anywhere US-Anywhere Location: St. Louis,MO
          

Data Scientist I (Mid Level)

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PURPOSE OF JOB

Uses advanced techniques that integrate traditional and non-traditional datasets and method to enable analytical solutions; Applies predictive analytics, machine learning, simulation, and optimization techniques to generate management insights and enable customer-facing applications; participates in building analytical solutions leveraging internal and external applications to deliver value and create competitive advantage; Translates complex analytical and technical concepts to non-technical employees

JOB REQUIREMENTS

* Partners with other analysts across the organization to fully define business problems and research questions; Supports SME's on cross functional matrixed teams to solve highly complex work critical to the organization.

* Integrates and extracts relevant information from large amounts of both structured and unstructured data (internal and external) to enable analytical solutions.

* Conducts advanced analytics leveraging predictive modeling, machine learning, simulation, optimization and other techniques to deliver insights or develop analytical solutions to achieve business objectives.

* Supports Subject Matter Experts (SME's) on efforts to develop scalable, efficient, automated solutions for large scale data analyses, model development, model validation and model implementation.

* Works with IT to research architecture for new products, services, and features.

* Develops algorithms and supporting code such that research efforts are based on the highest quality data.

* Translates complex analytical and technical concepts to non-technical employees to enable understanding and drive informed business decisions.

MINIMUM REQUIREMENTS

* Master's degree in Computer Science, Applied Mathematics, Quantitative Economics, Statistics, or related field. 6 additional years of related experience beyond the minimum required may be substituted in lieu of a degree.

* 4 or more years of related experience and accountability for complex tasks and/or projects required.

* Proficient knowledge of the function/discipline and demonstrated application of knowledge, skills and abilities towards work products required.

* Proficient level of business acumen in the areas of the business operations, industry practices and emerging trends required.

Must complete 12 months in current position (from date of hire or date of placement), or must have manager's approval prior to posting.

*Qualifications may warrant placement in a different job level*

PREFERRED

* Expertise in experimental design, advanced statistical analysis, and modeling to discover key relationships in data and applying that information to predict likely future outcomes; fluent in regression, classification, tree-based models, clustering methods, text mining, and neural networks.

* Proven ability to enrich (add new information to) data, advise on appropriate course(s) of action to take based on results, summarize complex technical analysis for non-technical executive audiences, succinctly present visualizations of high dimensional data, and explain & justify the results of the analysis conducted.

* Highly competent at data wrangling and data engineering in SQL and SAS as well as advanced machine learning (ML) techniques using Python; comfortable in cloud computing environments (Azure, GCP, AWS).

* Hands-on experience developing products that utilize advanced machine learning techniques like deep learning in areas such as computer vision, Natural Language Processing (NLP), sensor data from the Internet of Things (IoT), and recommender systems; along with transitioning those solutions from the development environment into the production environment for full-time use.

* PhD in Computer Science, Applied Mathematics, Quantitative Economics, Operations Research, Statistics, or related field with coursework in advanced Machine Learning techniques (Natural Language Processing, Deep Neural Networks, etc).

* Fluent in deep learning frameworks and libraries (TensorFlow, Keras, PyTorch, etc).

* Highly skilled in handling Big Data (Hadoop, Hive, Spark, Kafka, etc).

* Experience in reinforcement learning, knowledge graphs and graph databases, Generative Adversarial Networks (GANs), semi-supervised learning, multi-task learning is a plus.

* Experience in publishing at top ML, computer vision, NLP, or AI conferences and/or contributing to ML/AI-related open source projects and/or converting ML/AI papers into code is a plus.

* Background in Property insurance operations with an understanding of claims, underwriting, and insurance pricing a plus.

* Additional Skills: Ability to translate business problems and requirements into technical solutions by building quick prototypes or proofs of concept with business and technical stakeholders.

* Ability to convert proofs of concept into scalable production solutions.

* Ability to lead teams by following best practices in development, automation, and continuous integration / continuous deployment (CI/CD) methods in an agile work environment.

* Ability to work in and with technical, multidisciplinary teams.

* Willingness to continuously learn and apply new analytical techniques

RELOCATION assistance is AVAILABLE for this position.

The above description reflects the details considered necessary to describe the principal functions of the job and should not be construed as a detailed description of all the work requirements that may be performed in the job.

Must complete 12 months in current position (from date of hire or date of placement), or must have manager s approval prior to posting.

LAST DAY TO APPLY TO THE OPENING IS 11/06/19 BY 11:59 PM CST TIME.

USAA is an equal opportunity and affirmative action employer and gives consideration for employment to qualified applicants without regard to race, color, religion, sex, national origin, age, disability, genetic information, sexual orientation, gender identity or expression, pregnancy, veteran status or any other legally protected characteristic. If you'd like more information about your EEO rights as an applicant under the law, please click here. For USAA s Affirmative Action and EEO statement, please click here. Furthermore, USAA makes hiring decisions compliant with the Fair Chance Initiative for Hiring Ordinance (LAMC 189.00).

USAA provides equal opportunity to qualified individuals with disabilities and disabled veterans. If you need a reasonable accommodation, please email HumanResources@usaa.com or call 1-800-210-USAA and select option 3 for assistance.
          

Yabroudi Endowed Professorship in Sustainable Civil Infrastructure

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SYRACUSE -UNIVERSITY -ENGINEERING -& COMPUTER -SCIENCE Yabroudi Endowed Professorship in Sustainable Civil Infrastructure Syracuse University - The College of Engineering and Computer Science (ECS) and the Department of Civil and Environmental Engineering (CIE) at Syracuse University (SU) invite applications and nominations for the appointment of the Abdallah H. Yabroudi Professorship in Sustainable Civil Infrastructure. Candidates should have a strong background in construction/ sustainable construction asset management, project management and delivery, sustainable building practices, public -private partnership, or other closely related areas. In addition, candidates should have interest in internationalism, and the creation and development of civil infrastructure in emerging economies. - As part of the Invest Syracuse initiative (the University is implementing an ambitious and aggressive plan to hire 100 new faculty over the next five years to collaborate with existing faculty in multidisciplinary cluster areas focused on many of the grand challenges of this century. Several cluster areas have been identified and may be of interest to the Yabroudi Chair including Artificial Intelligence, Energy and Environment; Innovation and Entrepreneurship; Deep Learning, Autonomous Systems and Policy; Big Data and Data Analytics; Social Differences, Social Justice. The University has also recently committed to an interdisciplinary initiative in Public Infrastructure with the launch of the Syracuse University Infrastructure Institute (The Institute is dedicated to integrating and supporting research and academic programing with a focus on infrastructure across all the schools and colleges of the University. - Candidates for the Yabroudi Professorship should be exceptional faculty members with international experience, a distinguished record of scholarship with a funded research program, as well as a global perspective on sustainable civil infrastructure, particularly in emerging countries. Candidates should be deeply invested in the success of students. A PhD in engineering or a closely related field is required. A record of excellence in teaching and mentorship are critical to this appointment. Appointment of the Yabroudi Professor would be at the associate or full professor level. - The -CIE -Department (currently has 17 full-time faculty members engaged in teaching and research in construction, environmental, geotechnical, and structural engineering. The Department offers -ABET -accredited B.S. degrees in both Civil and Environmental Engineering, as well as M.S. and Ph.D. degrees in Civil and Environmental Engineering with approximately 250 undergraduate and 100 graduate students in these programs. The Department has close ties with other Departments within the College and across the University, including joint graduate certificate programs in Public Infrastructure Management and Leadership with the Maxwell School of Citizenship and Public Affairs, Sustainable Enterprise with the Whitman School of Management, and Enterprise Technology Leadership with the School of Information Studies and the Whitman School of Management. For more information on the College of Engineering and Computer Science and the Civil and Environmental Engineering Department at SU, please visit - For full consideration, applicants are required to complete an online application at under job number 074366. Please submit your cover letter, CV, a statement of teaching and research interests, and names and contact information for three professional references. Sample publications and other supporting materials may also be submitted. Review of applications will begin as soon as they are received and applications will be accepted until the position is filled. Nominations and inquiries should be directed to: Charles Driscoll, University Professor, Department of Civil and Environmental Engineering, 151 Link Hall, Syracuse University, Syracuse, NY 13244, . - Syracuse University is an equal opportunity/affirmative action employer with a strong commitment to equality of opportunity and a diverse work force. Women, military veterans, individuals with disabilities, and members of other traditionally underrepresented groups are encouraged to apply.The Chronicle of Higher Education. Keywords: Engineering - Associate Professor, Location: Syracuse, NY - 13244
          

2019 11 06 14 01 37

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Dive into Deep Learning, by Alex Smola and coll. Blog post here.
          

Book review: Deep learning with Python by François Chollet

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Deep learning with Python by Froncois Chollet is the third book I have reviewed on deep learning neural networks. Despite these reviews only spanning a couple of years it feels like the area is moving on rapidly. The biggest innovations I see from this book are in the use of pre-trained networks, and the dominance of …

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Senior Computer Vision Researcher

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Baidu Research General AI team (GAIT) is looking for an outstanding senior researcher with strong background in computer vision, machine learning, deep learning. Our mission is to research and develop next generation artificial intelligence (AI) technologies for image and video understanding as well as related products in cloud, intelligent cameras and robots. As a senior researcher at Baidu, you will be uniquely positioned in our team to work on different industry problems and to push forward frontiers of AI technologies. Publications in premier conferences or journals are also highly encouraged.

Qualifications:


  • PhD (or master with at least 5 years' working experience) in Computer Science, EE, Applied Mathematics, or related fields.
  • Strong publication record in premier AI-related venues such as CVPR, ICCV, ECCV, NIPS, PAMI, TIP or other related major conferences or journals.
  • Strong analytical and problem-solving skills.
  • Team player with good communication skills.
  • Strong coding skill with Python, CUDA, C/C++ and so on.

    Preferred knowledge/skills:


    • Experience in neural architecture search
    • Experience in neural model compression
    • Experience in human pose understanding and so on

          

AI/ML Executive Architect

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Summary / DescriptionUnisys is seeking candidates to make a difference by providing meaningful solutions to help our government secure the nation and fulfill the mission of government most effectively and efficiently. We are looking for candidates for Artificial Intelligence/Machine Learning Executive Architect role for our corporate office in Reston, VA.--The role of an AI/ML Solution Executive includes:--- Educates Unisys Federal Delivery Leadership, our existing clients and prospects as to emerging opportunities to apply AI/ML analytics to better leverage government data to make more timely and better mission decisions--- Provides the AI/ML vision for Unisys Federal--- Participates actively in providing technical leadership for AI/ML opportunities in the new business development cycle from deal identification, participating in call plans, driving solution strategy, in responding to a solicitation and in participating in tech challenges/hackathons to showcase our AI/ML skills--- Working with Unisys business development, program teams, capture and account teams to engage customers to best understand their AI/ML needs and to present Unisys capabilities, offerings and solutions in a compelling manner, thereby shaping customer perspectives --- Leads the establishment and sustainment of Unisys portfolio of capabilities for AI/ML, including marketing literature, proposal content, BoE/rate cards, proof points, reference architectures and proofs of concept/demoware--- Provides deep domain expertise regarding AI/ML, data modeling, enterprise data warehousing, data integration, data quality, master data management, statistical analyses of primarily structured datasets--- Provides deep domain expertise of AI/ML algorithms, tooling and solutions to solve mission problems for Unisys Federal clients--- Provides expertise in building government oriented solutions leveraging NoSQL solutions, big data (Hadoop/Apache Spark), Geographic Information Systems (GIS), key-value pair, columnar, graph, search, natural language processing, data science, machine learning and data visualization --- Drives market demand for AI/ML solutions by providing concise messages tailored for Unisys customers and their desired outcomes--- Defines our go to market strategy for AI/ML --- Collaborates closely with our corporate solutions organizations and alliance partners to incubate, design and deliver AI/ML offerings--- Curates proof points and past performance qualifications for Unisys success stories for applying AI/ML capabilities supporting the mission of government--- Identifies market trends in technology for AI/ML solutions--- Collaborates with Unisys Commercial Solutions organizations to prioritize corporate investments in AI/ML solutions--- Works with business units in tailoring capability strategies specific for them and work with appropriate government relationships to shape agency procurement--- Shapes procurements through presentations to clients and other speaking engagements --- Determines which alliances to pursue and events for Unisys to participate The AI/ML Executive is intimately familiar with market trends, helps to define go to market strategy and ensure that Unisys is in a position to be the best choice for meeting our customers--- AI/ML needs through collaboration with customers, partners, and internal stake holders to understand the requirements and connect them with Unisys capabilities and offerings.RequirementsRequired Skills:--- Master's degree and 20 years of relevant experience or equivalent--- Strong expertise in designing and delivering AI/ML/Deep Learning solutions--- Expertise and experience implementing technology solutions in four or more of the following areas: database design, data warehousing, data governance, metadata management, big data, noSQL, data science, data analytics, machine learning, natural language processing, streaming data.--- Experience with scientific scripting languages (e.g. Python, R) and object oriented programming languages (e.g. Java, C#) --- Strong expertise with machine learning and deep learning models and algorithms--- Solid grounding in statistics, probability theory, data modeling, machine learning algorithms and software development techniques and languages used to implement analytics solutions--- Deep experience with data modeling and Big Data solution stacks--- Deep knowledge in enterprise IT technologies, including databases, storage, and networks--- Deep experience with one or more Deep Learning frameworks such as Apache MXNet, TensorFlow, Caffe2, Keras, Microsoft Cognitive Toolkit, Torch and Theanu--- Has a successful track record in providing technical leadership in federal new business pursuits --- In-depth understanding of application, cloud, middleware, data management and system architecture concepts; experience leading the design and integration of enterprise-level technical solutions. --- Experience in capturing technical requirements and defining technical solutions in the form of conceptual, logical, and physical designs, including the ability to articulate those concepts verbally, graphically and in writing. --- Ability to synthesize solution design information, architectural principles, available technologies, third-party products, and industry standards to formulate a system architecture that meets client requirements and can be delivered within the desired timeframe. --- Experience developing cost models, technical delivery plans, technical solutions and basis of estimates (BOEs), including BOM development. Also develop concept of operations and discuss these models in Agile, federal SDLC or ITIL based terms. --- Experience identifying potential design, performance, security, and support problems, including ability to identify technical risks/challenges and develop relevant mitigation strategies. --- Extensive knowledge of the broad spectrum of technology areas, including technology trends, forthcoming industry standards, new products, and the latest solution development techniques; ability to leverage this knowledge to formulate technical solution strategy. --- Ability to consistently apply architectural guidelines when creating new solution architectures. --- Ability to develop integrated technology requirements project plan. --- Ability to interface with team members at all levels, including business operations, finance, technology, and management. --- Was primary author for a technical conference or whitepaper submission. (to be provided)Desired Qualifications --- Certifications from leading analytics platform providers (Cloudera, Horton, Databricks, AWS, Microsoft, etc.) --- Experience in leading remote teams in building demonstrations and proofs of concept--- Experience in classical DMBOK data management practices including data governance, data quality management, master data management, metadata management practices and tools--- Deep knowledge of Federal domain-specific data formats and structures, data storage, retrieval, transport, optimization, and serialization schemes--- Demonstrated experience developing engineering solutions for both structured and unstructured data, including data search. --- Experience working with very large (petabyte scale) datasets including data integration, analysis and visualization--- Experience with data integration and ETL tools (e.g. Apache NiFi, SSIS, Informatica, Talend, Azure Data Factory)--About UnisysDo you have what it takes to be mission critical? Your skills and experience could be mission critical for our Unisys team supporting the Federal Government in their mission to protect and defend our nation, and transform the way government agencies manage information and improve responsiveness to their customers. --As a member of our diverse team, you---ll gain valuable career-enhancing experience as we support the design, development, testing, implementation, training, and maintenance of our federal government---s critical systems. Apply today to become mission critical and help our nation meet the growing need for IT security, improved infrastructure, big data, and advanced analytics.Unisys is a global information technology company that solves complex IT challenges at the intersection of modern and mission critical. We work with many of the world's largest companies and government organizations to secure and keep their mission-critical operations running at peak performance; streamline and transform their data centers; enhance support to their end users and constituents; and modernize their enterprise applications. We do this while protecting and building on their legacy IT investments. Our offerings include outsourcing and managed services, systems integration and consulting services, high-end server technology, cybersecurity and cloud management software, and maintenance and support services. Unisys has more than 23,000 employees serving clients around the world. Unisys offers a very competitive benefits package including health insurance coverage from first day of employment, a 401k with an immediately vested company match, vacation and educational benefits. To learn more about Unisys visit us at www.Unisys.com.Unisys is an Equal Opportunity Employer (EOE) - Minorities, Females, Disabled Persons, and Veterans.#FED#
          

Medizinische Bildgebung: schnelleres Bild, gleiche Qualität

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Sie promoviert an der FAU auf dem Gebiet der quantitativen MR-Bildgebung in Kombination mit Deep Learning und hat eine auf Deep Learning basierende Rekonstruktionsmethode für die quantitative Bildtechnik Magnetic Resonance Fingerprinting entwickelt. Dafür ist Elisabeth Hoppe vom Lehrstuhl für Mustererkennung von der Gesellschaft für Informatik als KI-Newcomerin des Jahres nominiert...
          

Tomra presenta en Ecomondo un complemento adicional para sus máquinas de clasificación basadas en 'deep learning'

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Tomra Sorting Recycling lanza su nueva tecnología de clasificación basada en 'deep learning', llamada GAIN, con la que se gana mayor capacidad de rendimiento de sus máquinas de clasificación basada en sensores. La tecnología GAIN se ofrece como ...
          

Sr. Research Scientist, Reinforcement Learning

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Changing the world through digital experiences is what Adobe s all about. W give everyone from emerging artists to global brands everything they n to design and deliver exceptional digital experiences. We re passionate abo empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours. Take a peek into Adobe life in this video. The challenge The Cloud Technology organization builds platform and client services that are foundational building blocks for many other Adobe products and services. Areas of focus include: identity, security, cloud storage, e-commerce, workflow management, synchronization, customer facing web apps, scalability, infrastructure management and search, just to name a few. Our mission is to build highly scalable, highly available and highly resilient services that fulfill the business objectives of Adobe The Data Science Lab (DSL) at Adobe Research, San Jose, is looking to hire an established researcher in the broad area of multi-armed bandits, reinforcement learning, sequential decision-making, and probabilistic planning. The successful candidate should have credentials that are preferably at the senior research scientist level. This is an opportunity to work alongside an established world class team of researchers with expertise in reinforcement learning, sequential decision making, multi-armed bandits, optimization, game theory, sketching and streaming algorithms, causation, counterfactuals and imagination-based AI. DSL has an excellent publication record with dozens of papers at top-tier machine learning and AI conferences and journals in recent years. Over the past few years, Adobe has had a world class team in RL, with a highly successful track record of publications in top AI and ML conferences. With more than 170 world-class research scientists and engineers, Adobe Research blends cutting-edge academic discovery with industry impact. Our scientists are provided with the resources, support, and freedom to shape their ideas into innovative technologies. They collaborate with colleagues at over fifty universities, often presenting their work at top-tier international conferences. Many of our researchers discoveries are incorporated into Adobe s products, building the company s reputation as a pioneer in co and data intelligence. Adobe is one of the largest software companies in the world, and a market leader in three major areas: Creative Cloud (Photoshop, Illustrator, Spark etc.), Document Cloud (PDF and related software), and the Digital Experience Cloud (including Adobe Audience Manager, Adobe Analytics, Target, and Campaign). Adobe Experience Cloud (******************************************* is one of the largest data collection platforms in the world, managing the content, customer intelligence, and digital marketing for most Fortune 500 companies. Adobe Digital Experience cloud processes trillions of transactions per year, involving hundreds of petabytes of data, and offers unparalleled opportunities for exploring web scale solutions for AI and machine learning. The role * Help drive the technical agenda in reinforcement learning and related topics. * Responsible for providing technical leadership across multiple teams, by understanding the technical space deeply enough to help guide corporate strategy or business unit strategy, or by providing innovations that fuel the growth of Adobe. * Be able to lead cross functional working groups or initiatives or provide consulting/advice to other departments or groups within the company * Partner with the already existing research teams at Adobe, including world class experts in computer vision, deep learning, NLP, graphics, and HCI * Provide critical analysis of issues for continuous improvement of technology, process and team productivity * Act as an industry evangelist, internally and externally. Engage with the research community at large, including university collaborations, intern recruiting and mentorship, and publishing and participation in top-tier conferences. The_Requirements * Five or more years of experience and a PhD in Machine Learning, Artificial Intelligence or related field * Prior experience in the development of current or future products or technologies * Recognized by peers in industry, academia or the research community * Recognized technical expertise includes but not limited to publications, editorial and advisory boards, conference/symposium presentations, patents, professional peer recognition and strategically important developments, innovations, or technical contributions * Demonstrated experience in mentoring and coaching interns, and junior technical contributors. Application Submission The application should include a brief description of the applicant's research interests and experience, plus a CV that contains the degrees, relevant publications, names and the contact information of references, and other relevant documents. At Adobe, you will be immersed in an exceptional work environment that is recognized throughout the world on Best_Companies_lists. You will also be surrounded by colleagues who are committed to helping each other grow through our unique Check-In approach where ongoing feedback flows freely. If you re looking to make an impact, Adobe's the place for you. Discover wh our employees are saying about their career experiences on the Adobe Life blog and explore the meaningful benefits we offer. Adobe is an equal opportunity employer. We welcome and encourage diversity in the workplace regardless of race, gender, religion, age, sexual orientation, gender identity, disability or veteran status.
          

Principal Technical Product Manager - Telecom OSS/BSS Applications and Services - Amazon.com Services, Inc. - Bellevue, WA

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Machine Learning and Deep Learning applicability to Telecom services. Strong understanding of business flows and integrated up stream & downstream applications.
From Amazon.com - Fri, 09 Aug 2019 07:52:12 GMT - View all Bellevue, WA jobs
          

Deep Learning and NLP A-Z How to create a ChatBot

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Deep Learning and NLP A-Z How to create a ChatBot

Category: Tutorial

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Speech Processing for Digital Home Assistants: Combining signal processing with deep-learning techniques

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Once a popular theme of futuristic science fiction or far-fetched technology forecasts, digital home assistants with a spoken language interface have become a ubiquitous commodity today. This success has been made possible by major advancements in signal processing and machine learning for so-called far-field speech recognition, where the commands are spoken at a distance from the sound-capturing device. The challenges encountered are quite unique and different from many other use cases of automatic speech recognition (ASR). The purpose of this article is to describe, in a way that is amenable to the nonspecialist, the key speech processing algorithms that enable reliable, fully hands-free speech interaction with digital home assistants. These technologies include multichannel acoustic echo cancellation (MAEC), microphone array processing and dereverberation techniques for signal enhancement, reliable wake-up word and end-of-interaction detection, and high-quality speech synthesis as well as sophisticated statistical models for speech and language, learned from large amounts of heterogeneous training data. In all of these fields, deep learning (DL) has played a critical role.
          

026 – Gordon Wilson

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Gordon Wilson is the CEO of Rain Neuromorphics, a company developing neuromorphic computer chips to enable brain-like artificial intelligence. Gordon holds a B.S. in Statistics and Mathematics from the University of Florida. Top 3 Takeaways Training deep learning algorithms is expensive. To understand...
          

NVIDIA เปิดตัว Jetson Xavier NX ชิปประมวลผล AI ขนาดเล็กสำหรับอุปกรณ์ปลายทาง

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NVIDIA เปิดตัว Jetson Xavier NX ชิปซุปเปอร์คอมพิวเตอร์สำหรับประมวลผล AI ที่ NVIDIA บอกว่าเล็กที่สุดในโลกด้วยขนาด 70x45 มิลลิเมตร สำหรับการประมวลผลในอุปกรณ์ปลายทาง (the edge) ในอุปกรณ์ประเภทฝังตัว (embeded device) หรือหุ่นยนต์ต่าง ๆ

NVIDIA บอกว่า Xavier NX มีกำลังประมวลผลสูงสุด 21 TOPS ที่กำลังไฟ 15W (ส่วนไฟ 10W จะสามารถประมวลผลได้ที่ 14 TOPS) ซีพียูเป็น ARM64 สถาปัตยกรรม Carmel 6 คอร์ จีพียู NVIDIA Volta มี CUDA Core 384 คอร์ และ Tensor Core อีก 48 คอร์ และ NVDLA ตัวเร่งการประมวลผล Deep Learning 2 ตัว แรม LPDDR4x 128-bit ขนาด 8GB

ราคาของ Jetson Xavier NX อยู่ที่ 399 เหรียญ จะเริ่มผลิตและวางขายเดือนมีนาคมปี 2020 ที่จะถึงนี้

ที่มา - NVIDIA, NVIDIA Dev Blog

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Oracle Veritabanında SQL ile Deep Learning Modeli Geliştirmek : Predicting Boston House Prices

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Herkese Selam, Bu yazıda Oracle 18c’nin ileri analitik opsiyonlarına getirdiği yeni algoritmalardan biri olan Neural Networkleri kullanarak bir deep learning modeli kurup basit bir regresyon (Regression) analizi yapacağım. Umarım farkındalık anlamında faydalı bir yazı olur. Veri Bilimi ve Makine Öğrenmesi … Continue reading
          

דרושים פרילנסרים לפיתוח python מת"א וגם מרחוק

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חברה בתל אביב המפתחת מוצר המספק הגנת סייבר באמצעות deep learning, כותבים מערכת לניהול קונפיגורציה, מחפשים איש Python חזק מאוד שיכול להרים עצמאית פרויקט תוך כחודש, שיכלול עבודה בענן (גוגל ואמזון).נדרש ניסיון של מינימום 4 שנים בפיתוח ב Python. ניסיון עם MongoDB ו Redis.יש פוטנציאל להמשכיות בצוות של ה- back endהיקף - משרה מלאה או קצת פחות, יש מקום לחלק מהזמן עבודה מרחוק.
          

Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research

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In recent years, the development of high-throughput screening (HTS) technologies and their establishment in an industrialized environment have given scientists the possibility to test millions of molecules and profile them against a multitude of biological targets in a short period of time, generating data in a much faster pace and with a higher quality than before. Besides the structure activity data from traditional bioassays, more complex assays such as transcriptomics profiling or imaging have also been established as routine profiling experiments thanks to the advancement of Next Generation Sequencing or automated microscopy technologies. In industrial pharmaceutical research, these technologies are typically established in conjunction with automated platforms in order to enable efficient handling of screening collections of thousands to millions of compounds. To exploit the ever-growing amount of data that are generated by these approaches, computational techniques are constantly evolving. In this regard, artificial intelligence technologies such as deep learning and machine learning methods play a key role in cheminformatics and bio-image analytics fields to address activity prediction, scaffold hopping, de novo molecule design, reaction/retrosynthesis predictions, or high content screening analysis. Herein we summarize the current state of analyzing large-scale compound data in industrial pharmaceutical research and describe the impact it has had on the drug discovery process over the last two decades, with a specific focus on deep-learning technologies.


          

Neuromorphic: A Step Towards Artificial Intelligence?

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Today, the neuromorphic approach still occupies the ‘curio cabinet’. “Many are prophesying the advent of neuromorphic approaches in the same way deep learning techniques were wrongfully dismissed – until they ended up reigning,” explained Pierre Cambou, Principal Analyst, Imaging at Yole Développement (Yole).

The post Neuromorphic: A Step Towards Artificial Intelligence? appeared first on eeDesignIt.com.


          

Inteligencia Artificial aplicada al reciclaje: TOMRA presenta un complemento para sus máquinas de clasificación basado en deep learning

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  La tecnología GAIN, presentada en la feria Ecomondo, permite lograr una clasificación compleja con mayor precisión a rendimientos más altos. TOMRA Sorting Recycling lanza su nueva tecnología de clasificación basada en deep learning, llamada GAIN, con la que se gana mayor capacidad de rendimiento de sus máquinas de clasificación basada en sensores. La tecnología … Continue leyendo »

Esta noticia: Inteligencia Artificial aplicada al reciclaje: TOMRA presenta un complemento para sus máquinas de clasificación basado en deep learning está completa en Residuos Profesional.


          

DataToBiz - ETL Engineer (2-6 yrs) Chandigarh (Backend Developer)

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We are a team of young and dynamic professionals looking for an exceptional Data Engineer to join our team in Chandigarh. We are trying to solve some very exciting business challenges by applying cutting-edge Big Data, Machine Learning and Deep Learning Technologies. Being a consulting and services startup we are looking for quick learners who can work in a cross-functional team of Consultants,...
          

Pour Le Deep Learning De La Regression Lineaire A L Apprentissage Par Renforcement Reza Bosagh Zadeh Bharath

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Pour Le Deep Learning De La Regression Lineaire A L Apprentissage Par Renforcement Reza Bosagh Zadeh Bharath
          

Improving Performance of Devanagari Script Input-Based P300 Speller Using Deep Learning

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G. B. Kshirsagar , N. D. Londhe In P300 based BCI systems, eliciting ERP using the oddball stimulation will conceal the original P300...
          

Applying NLP in Java: All From the Command-Line

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Learn more about NLP in Java!

We are all aware of machine learning tools and cloud services that work via the browser and give us an interface we can use to perform our day-to-day data analysis, model training, evaluation, and other tasks to various degrees of efficiencies.

But what would you do if you wanted to run these tasks on or from your local machine or infrastructure available in your organization? And, if these resources available do not meet the pre-requisites, to do decent end-to-end data science or machine learning tasks. That’s when access to a cloud-provider agnostic, deep learning management environment like Valohai can help. And to add to this, we will be using the free-tier that is accessible to anyone.


          

DIGI-TECH PHARMA & AI 2020

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The 4th Annual Digi-Tech Pharma & AI conference brings with it even more interactive sessions, expert speakers, senior professionals and decision makers from leading pharma, bio-tech and healthcare industry. Meet the decision makers, benchmark and learn from real-life use cases to drive organizational change and to understand the new cutting-edge technologies and practical solutions. In this 4th edition as we explore the novel technologies and developments reforming pharmaceutical industry, we also dive deep into the implementation and advances in machine learning, deep learning, artificial intelligence, informatics and data science which has redefined the development of new drugs, tackle diseases, improving healthcare and much more. The enhancements in data management and data integration are providing improvements to both the speed and quality of drug discovery and many clinical trial processes. To be in the forefront, a necessity for partnership and collaboration with healthcare provider is a must for the pharmaceutical companies, and these partnerships will also lead to massive advances in R&D using artificial intelligence in genomics and precision medicine to develop a deep understanding of the root causes of diseases. The combination of AI, big data and IoT technologies are creating new innovations, also other eminent technologies like cloud computing, augmented reality, virtual reality and blockchain are being used extensively in the Pharmaceutical industry’s digital transformation. It gives us a great pleasure to welcoming you to this international pharmaceutical technology conference 4th Annual Digi-Tech Pharma & AI 2020. KEY HIGHLIGHTS : Digital Technology trends in Pharma and Bio-Tech industry Adopting AI and Machine Learning to unlock the full potential of Pharma How pharma can integrate into digital health environment Collaborative Innovation: Finding the right partners to leverage new technologies in Pharma Patient Centred Drug Discovery Applying AI to the design of lead compounds for new drugs Algorithms and Models for drug discovery AI and ML for Target Identification & Validation in Drug Discovery Advancing Drug Discovery through quantum computing Genomics & Drug Discovery Virtual and Hybrid Clinical Trials R&D Use Cases Implementation and relevance of FAIR data principles in Pharma R&D Harnessing Data Science for Drug Combination Discovery AI and Big Data: A powerful combination for future growth The use of AI to make sense of clinical data Use of big data for precision medicine Multi-omics & clinical data to unlock the power of complex datasets Integration and Visualization of translational Medicine Data Data & Healthcare Analytics The Growing Importance of Real-World Data RWD for clinical research and drug development RWE and RWD to support regulatory decision making Real?World Data Science to advance Patient Care Managing real world data governance Healthcare & Medical Technology Adoption of IoT in Pharma Potential of Cloud Computing in Pharma Impact of Digital Health in Pharma Digital Health strategy and Patient centric Clinical Trials The convergence of Digital Therapeutics and Pharma in Digital Health How pharma-health collaboration works on innovating drug discovery & patient experience Blockchain and AI-based Platform WHO SHOULD ATTEND THE CONFERENCE: This event is designed for senior level attendees from various companies including pharmaceutical, biotechnological, biopharmaceutical, CRO’s, Diagnostics, solution provider and government institutions. Attendees includes Chief Data Officer, VPs, GMs, Directors, Heads and Managers of • Drug Delivery Innovation • R&D IT • Big Data Solutions • AI/ Machine Learning • Cognitive Computing • Digital innovative strategic planning • Genomics & Drug Discovery • Virtual and Hybrid Clinical Trials • Real-World Data • Real-World Evidence • Data Management & Analytics • Data Sciences • Clinical trials and data management • Translational informatics • Data storage and analysis • Enterprise Architecture • Information Systems • Contract outsourcing service providers • Digital Health • Healthcare IT • Computational Biology • Multi-channel Management • Blockchain and AI-based Platform
          

NVIDIA Provides U.S. Postal Service AI Technology to Improve Delivery Service

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GTC DC  -- NVIDIA today announced that the United States Postal Service – the world's largest postal service, with 485 million mail pieces processed and delivered daily – is adopting end-to-end AI technology from NVIDIA to improve its package data processing efficiency. The new system starts with high-performance servers powered by NVIDIA V100 Tensor Core GPUs and deep learning software to train multiple AI algorithms. The trained models are then deployed to NVIDIA EGX edge computi...

Read the full story at https://www.webwire.com/ViewPressRel.asp?aId=249532


          

Machine Learning From Scratch Through Python

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This course is for those who want to step into Artificial Intelligence domain, specially into Machine Learning, though I will be covering Deep Learning in deep as well. This is a basic course for beginners, just if you can get basic knowledge of Python that would be great and helpful to you to grasp things […]

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Embedded Vision Europe Conference: Representing international value chain

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Organized by the EMVA and Messe Stuttgart, the Embedded Vision Europe 2019 (eVe) conference attracted over 130 international conference attendees from 23 countries from 24 – 25 October at the ICS Stuttgart. They represented the entire value chain from deep learning and AI developers, machine vision players to users of embedded vision systems and even stakeholders from the financial sector. The presentation program included the full spectrum of the embedded vision industry, covering...

          

Machine Vision Market Is Expected to Grow at a CAGR of 7.1% 2019 to 2025

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According to a recent report, The Global Machine Vision Market is expected to reach USD 14.0 billion by 2024 from an estimated USD 9.9 billion in 2019, at a CAGR of 7.1% from 2019 to 2024. Top Leading Companies are Cognex Corporation, Basler, Teledyne DALSA, OMRON, Keyence, Datalogic, Edmund Optics, Allied Vision Technologies The recent advancements in imaging technology such as deep learning software, liquid lens, vision processing unit, 360-degree camera, hyperspectral imaging, and hybrid...

          

Cognex Acquires SUALAB, Deep Learning Specialist

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Cognex Corporation, a specialist in machine vision for factory automation and industrial barcode reading, today announced the acquisition of SUALAB, a leading Korean-based developer of vision software using deep learning for industrial applications. The addition of SUALAB’s engineering team and intellectual property is expected to enhance Cognex’s existing deep learning capabilities based on technology acquired from ViDi Systems in April of 2017. “Deep learning enables...

          

Framos' AI Vision Spin-off Changes Name to cubemos

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The Framos Group, a global supplier of imaging products, custom vision solutions, and OEM services, is announcing that its spin-off Framos AI will become cubemos. The cubemos entity focuses on deep learning and AI development, helping industrial customers to integrate leading-edge AI vision solutions. cubemos designs and implements proximal edge applications with AI functionality, providing innovative software solutions and products around imaging and AI. The Munich based company, as part of...

          

Deep Learning for Detection of Cancerous and Precancerous Esophagus Tissue

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This diagnostic study describes a novel attention-based deep neural network framework for classifying microscopy images to identify Barrett esophagus and esophageal adenocarcinoma.
          

Deep Learning at Scale with Nearest Neighbours Communications

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Title: Deep Learning at Scale with Nearest Neighbours Communications Abstract: As deep learning techniques become more and more popular, there is the need to move these applications from the data scientist’s Jupyter notebook to efficient and reliable enterprise solutions. Moreover, distributed training of deep learning models will happen more and more outside the well-known borders of cloud and HPC infrastructure and will move to edge and mobile platforms. Current techniques for distributed deep learning have drawbacks in both these scenarios, limiting their long-term applicability. After a critical review of the established techniques for Data Parallel training from both a distributed computing and deep learning perspective, a novel approach based on nearest-neighbour communications is presented in order to overcome some of the issues related to mainstream approaches, such as global communication patterns. Moreover, in order to validate the proposed strategy, the Flexible Asynchronous Scalable Training (FAST) framework is introduced, which allows to apply the nearest-neighbours communications approach to a deep learning framework of choice. Finally, a relevant use-case is deployed on a medium-scale infrastructure to demonstrate both the framework and the methodology presented. Training convergence and scalability results are presented and discussed in comparison to a baseline defined by using state-of-the-art distributed training tools provided by a well-known deep learning framework.
          

Big Data et Machine Learning : Les concepts et les outils de la data science Ed. 3

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Auteur : Lemberger, Pirmin
Editeur : Dunod

Cet ouvrage s’adresse à tous ceux qui cherchent à tirer parti de  l’énorme potentiel des technologies Big Data, qu’ils soient data  scientists, DSI, chefs de projets ou spécialistes métier.Le Big Data s’est imposé comme une innovation majeure pour  toutes les entreprises qui cherchent à construire un avantage  concurrentiel de l’exploitation de leurs données clients,  fournisseurs, produits, processus, etc.Il a en outre permis l’émergence des techniques d’apprentissage  automatique (Machine Learning, Deep Learning…) qui ont  relancé le domaine de l’intelligence artificielle.Mais quelle solution technique choisir ? Quelles compétences  métier développer au sein de la DSI ?Ce livre est un guide pour comprendre les enjeux d’un projet Big  Data, en appréhender les concepts sous-jacents et acquérir les  compétences nécessaires à la mise en place d’une architecture  d’entreprise adaptée.Il combine la présentation :de notions théoriques (traitement statistique des données,  calcul distribué…) ;des outils les plus répandus ;d’exemples d’applications, notamment en NLP (Natural  Language Processing) ;d’une organisation typique d’un projet de data science.


          

Pour Le Deep Learning De La Regression Lineaire A L Apprentissage Par Renforcement Reza Bosagh Zadeh Bharath

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Pour Le Deep Learning De La Regression Lineaire A L Apprentissage Par Renforcement Reza Bosagh Zadeh Bharath
          

Get Ready For Big Data: TOMRA Introduces Deep Learning Add-On For Autosort Machines At Ecomondo

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GAIN, TOMRA’s deep learning-based sorting technology, for advanced accuracy of complex sorting tasks at high throughput rates.
          

Azure Machine Learning Pipelines | AI Show

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This video talks about Azure Machine Learning Pipelines, the end-to-end job orchestrator optimized for machine learning workloads. With Azure ML Pipelines, all the steps involved in the data scientist's lifecycle can be stitched together in a single pipeline improving inner-loop agility, collaboration, and reuse of data and code, while maintaining high reliability.

 Learn More: 

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Pour Le Deep Learning De La Regression Lineaire A L Apprentissage Par Renforcement Reza Bosagh Zadeh Bharath

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Pour Le Deep Learning De La Regression Lineaire A L Apprentissage Par Renforcement Reza Bosagh Zadeh Bharath
          

Deep Learning Sales Consultant - DeepLearningTeam - Virginia

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Identifies requests for proposals from businesses, governmental agencies or other organizations seeking to purchase customized software and assists Lazarus in.
From DeepLearningTeam - Sat, 24 Nov 2018 06:56:10 GMT - View all Virginia jobs
          

Tomra introduces deep learning add-on for autosort machines

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Gain, Tomra’s deep learning-based sorting technology, advances accuracy of complex sorting tasks at high throughput rates.
          

Caper Shopping Cart Scan-Pay-Go

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ด้วยรถเข็นชำระเงินอัจฉริยะที่ขับเคลื่อนโดยเทคโนโลยีอย่าง Deep Learning และ Computer Vision รายการสินค้าจะถูกตรวจจับได้ทันทีเมื่อถูกโยนเข้าไปในรถเข็น ลูกค้าสามารถโยนสินค้าเข้าไป จ่ายเงิน และ ออกจากร้านค้า โดยไม่ต้องต่อคิดอีกต่อไป ฟัง PodCast เรื่องเกี่ยวเทคโนโลยีใหม่ ๆ ได้ที่ Geek Forever’s Podcast——————————————–ฟังผ่าน Podbean :📌http://bit.ly/2m7CpC8——————————————–ฟังผ่าน Apple Podcast :📌https://apple.co/2lEqPPg——————————————–ฟังผ่าน Google Podcast :📌http://bit.ly/2kxHtQ3——————————————–ฟังผ่าน Spotify :📌https://spoti.fi/2m0PTzR——————————————–ฟังผ่าน Youtube :📌http://bit.ly/2mvEVTf——————————————–📌References : https://www.caper.ai/ ติดตาม ด.ดล Blog เพิ่มเติมได้ที่Fanpage :facebook.com/tharadhol.blogBlockdit :blockdit.com/tharadhol.blogTwitter :twitter.com/tharadholInstragram :instragram.com/tharadhol

The post Caper Shopping Cart Scan-Pay-Go appeared first on Geek Forever.


          

South Korean Company, Yuhan Pharmaceuticals Partners with Cyclica to Advance R&D Across Two Separate Programs for Oncology

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Nov 07, 2019

TORONTO & SEOUL, South Korea--(BUSINESS WIRE)--Renowned South Korean healthcare company, Yuhan Pharmaceuticals (Yuhan) and Cyclica Inc. (Cyclica), a leading neo biotechnology company announce a collaboration to apply Cyclica’s proprietary AI-integrated drug discovery platform in two separate R&D programs. Yuhan is keen on implementing innovative technologies to enhance drug development efforts and will utilize Cyclica’s unique end-to-end AI-integrated drug discovery platform across diverse therapeutic areas to develop novel advanced lead-like molecules with desired chemical properties against the targets of interest determined by Yuhan’s R&D priorities.

Yuhan will leverage Cyclica’s integrated drug discovery platform, Ligand DesignTM and Ligand Express® to generate novel chemical entities with desired polypharmacological, physicochemical, and ADMET properties while providing insights into systems biology and structural pharmacogenomics.

Cyclica will receive an upfront payment as well as receive milestone payments upon the completion of specific objectives. Through this collaboration, Yuhan and Cyclica envision a long-term relationship to enhance future R&D and drug discovery efforts to identify novel solutions for unaddressed therapeutic needs.

Yuhan CEO and President Jung Hee Lee said, “We are very pleased to be collaborating with Cyclica to apply its proprietary AI-integrated drug discovery platform in our R&D programs, and hope to expand our partnership upon the success of the collaboration. Yuhan is dedicated to offering first-in-class to the patients within a short time by applying new computational methods, including AI and Big Data that can shorten the time and the cost required for drug development.”

“It’s an honour to collaborate with Yuhan, a visionary company that is thinking deeply about the future of the discovery of better medicines, and the application of new computational methods, including machine and deep learning. I am confident that this collaboration, and the future relationship with Yuhan and Cyclica will benefit patients waiting for new and better medicines.” said Naheed Kurji, President and CEO of Cyclica.

About Yuhan Corporation.

Yuhan Corporation is a South Korea-based healthcare company founded in 1926. The company has positioned itself as one of the top pharmaceutical companies in terms of market cap and sales revenue in Korea. The core business consists of primary & specialty care, dietary supplements, household & animal care, and contract manufacturing of active pharmaceutical ingredients. It has a number of subsidiaries and a global presence in the form of joint ventures with the Clorox Company(USA) and Kimberly-Clark Corporation (USA). Yuhan (000100:KS) is a publicly-listed company traded on the Korea Stock Exchange.

About Cyclica Inc.

Cyclica is a Toronto-based, globally recognized biotechnology company that leverages AI and computational biophysics to reshape drug discovery. Cyclica provides the pharmaceutical industry with an integrated and end-to-end enabling drug discovery platform focused on polypharmacology. Ligand Design and Ligand Express offer a unique AI-augmented platform to design advanced lead-like molecules that minimize unwanted off-target effects, while providing a holistic understanding of a molecule's activity through integrated systems biology and structural pharmacogenomics. By doing more with artificial intelligence, Cyclica aims to revolutionize a system troubled with attrition and costly failures, accelerate the drug discovery process, and develop medicines with greater precision.

Contacts
Naheed Kurji
Naheed.Kurji@cyclicarx.com

Category: 
Collaboration / Partnership
Pharmaceuticals & Biotech
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Deep Learning: Nvidia stellt neues KI-Entwicklerboard vor

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Mit dem Jetson Xavier NX hat Nvidia eine neue Entwicklerplatine für den Machine-Learning-Sektor vorgestellt. Das Board soll beispielsweise in Robotern und beim Edge-Computing zum Einsatz kommen.

Seit 2014 bietet Nvidia unter dem Markennamen Jetson verschiedene Entwicklerboards für den Deep-Learning-Einsatz an. Mit dem Jetson Xavier NX hat der Hersteller das neuste Modell der Produktreihe vorgestellt. Jetson Xavier NX ist als Steckmodul ausgeführt, dessen Grundfläche etwas kleiner ausfällt als die einer Kreditkarte. Das Board ist mit dem Jetson Nano pin-kompatibel und soll daher gut für ...

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