Post-Doctoral Fellowship on Ethically Aligned Artificial Intelligence
Mila is looking for a postdoctoral fellow who would work on ethically aligned learning machines, or how an AI can acquire moral competence. The research topic is important in the long-term for AI safety, towards building machines which can achieve specific goals while acting in a way consistent with human values and social norms. The candidate should be able to perform experiments with data (e.g. to acquire or collect relevant data from humans) and train deep learning systems towards these goals. She or he must also be able to engage with some of the philosophical issues raised by artificial moral agents and the idea of moral competence for an AI system.
Priority will be given to candidates that have a substantial knowledge in machine learning, as well as in philosophy, moral psychology or the social sciences.
The position is for one year, with possibility of renewal, at Mila. The project will involve professors Bengio (University of Montreal) and Dominic Martin (UQAM) as well as other potential collaborators in machine learning and philosophy.
To apply, please submit requested documents at https://mila.quebec/en/admission/, and contact Professors Bengio (via his assistant at [email protected]) and Martin ([email protected]) by e-mail.
We will start processing applications as of September 16th 2019, and until the position is filled. Candidates are expected to start their fellowship during the Fall semester.
Mila is looking for a postdoctoral fellow who would work on ethically aligned learning machines, or how an AI can acquire moral competence. The research topic is important in the long-term for AI safety, towards building machines which can achieve specific goals while acting in a way consistent with human values and social norms. The candidate should be able to perform experiments with data (e.g. to acquire or collect relevant data from humans) and train deep learning systems towards these goals. She or he must also be able to engage with some of the philosophical issues raised by artificial moral agents and the idea of moral competence for an AI system.
Priority will be given to candidates that have a substantial knowledge in machine learning, as well as in philosophy, moral psychology or the social sciences.
The position is for one year, with possibility of renewal, at Mila. The project will involve professors Bengio (University of Montreal) and Dominic Martin (UQAM) as well as other potential collaborators in machine learning and philosophy.
To apply, please submit requested documents at https://mila.quebec/en/admission/, and contact Professors Bengio (via his assistant at [email protected]) and Martin ([email protected]) by e-mail.
We will start processing applications as of September 16th 2019, and until the position is filled. Candidates are expected to start their fellowship during the Fall semester.
Postdoctoral Position at Washington University (AI/ML for telemedicine)
We are seeking a full time Postdoctoral Research Associate / Scholar
to work on exciting projects at the intersection of machine learning
(ML), AI, and clinical decision support at Washington University in St
Louis. The candidate will work with massive real-time medical data
collected in a leading hospital, and will solve challenging problems
with significant impacts on next-general smart healthcare.
The Project
The goal of the TECTONICS (Telemedicine Control Tower for the OR:
Navigating Information, Care and Safety) project is to harness large
scale clinical data to improve the care of perioperative patients by
providing timely, explainable, and actionable ML predictions of
patient trajectories. The TECTONICS team is externally funded for a
randomized trial of integrated telemedicine and real-time risk
prediction for anesthesia providers.
TECTONICS is deeply interdisciplinary, including experts in ML, optimization, planning, big data mining, human-computer interaction, biostatistics, clinical informatics, and clinical trials. Currently the team consists of 6 full-time faculty members, 2 postdoctoral researchers, 3 PhD students, 1 informatics technicians, 1 clinical experts, and 3 staff members and we are seeking to hire 1-2 additional post-docs and research staff.
The candidate will take a leading role in refinement of existing methods
and development of novel techniques in ML for clinical prediction. The
candidate will be expected to pursue independent lines of research,
and should anticipate using one of the multiple clinical datasets
available to the TECTONICS team. The datasets contain detailed
electronic records and real-time operation data for hundreds of
thousands of patients. The candidate will co-supervise graduate
students and undergraduate research assistants, and be expected to
work closely with TECTONICS team members from other disciplines.
The Candidate
Successful candidates will hold an MD or PhD and have a strong
research record in machine learning and a strong interest in
developing practical systems for healthcare and medicine. Expertise
with time-series learning, interpretable and actionable learning,
online learning, dealing with imbalanced, noisy, and incomplete data,
knowledge embedding, and clinical data mining will be a plus. The
duties and responsibilities of this position include conducting
individual and collaborative research on the themes of the project,
developing novel algorithms and systems based on the needs of the
project, and producing high-quality outputs for publication in
high-profile journals or conference proceedings.
The position is initially for 2 years, with possible extension up to 5
years total. We offer a highly competitive benefits package including
training and development opportunities. Washington University in St.
Louis is one of the best places for this type of interdisciplinary
research on ML and AI in telemedicine and clinical decision-making.
The position is based in St. Louis, Missouri, USA where the university
is situated in a beautiful, leafy campus near the Forest Park and many
metropolitan activities. This is a full-time position, available from
July 2019 or as soon as possible thereafter.
To Apply
To apply, please send your CV to Maureen Arends at [email protected] .
Please mention the TECTONICS project in your email.
For any questions regarding this opportunity, please feel free to contact:
- Prof. Yixin Chen ([email protected]), Department of
Computer Science and Engineering
- Prof. Michael Avidan ([email protected]) , Department
of Anesthesiology
We are seeking a full time Postdoctoral Research Associate / Scholar
to work on exciting projects at the intersection of machine learning
(ML), AI, and clinical decision support at Washington University in St
Louis. The candidate will work with massive real-time medical data
collected in a leading hospital, and will solve challenging problems
with significant impacts on next-general smart healthcare.
The Project
The goal of the TECTONICS (Telemedicine Control Tower for the OR:
Navigating Information, Care and Safety) project is to harness large
scale clinical data to improve the care of perioperative patients by
providing timely, explainable, and actionable ML predictions of
patient trajectories. The TECTONICS team is externally funded for a
randomized trial of integrated telemedicine and real-time risk
prediction for anesthesia providers.
TECTONICS is deeply interdisciplinary, including experts in ML, optimization, planning, big data mining, human-computer interaction, biostatistics, clinical informatics, and clinical trials. Currently the team consists of 6 full-time faculty members, 2 postdoctoral researchers, 3 PhD students, 1 informatics technicians, 1 clinical experts, and 3 staff members and we are seeking to hire 1-2 additional post-docs and research staff.
The candidate will take a leading role in refinement of existing methods
and development of novel techniques in ML for clinical prediction. The
candidate will be expected to pursue independent lines of research,
and should anticipate using one of the multiple clinical datasets
available to the TECTONICS team. The datasets contain detailed
electronic records and real-time operation data for hundreds of
thousands of patients. The candidate will co-supervise graduate
students and undergraduate research assistants, and be expected to
work closely with TECTONICS team members from other disciplines.
The Candidate
Successful candidates will hold an MD or PhD and have a strong
research record in machine learning and a strong interest in
developing practical systems for healthcare and medicine. Expertise
with time-series learning, interpretable and actionable learning,
online learning, dealing with imbalanced, noisy, and incomplete data,
knowledge embedding, and clinical data mining will be a plus. The
duties and responsibilities of this position include conducting
individual and collaborative research on the themes of the project,
developing novel algorithms and systems based on the needs of the
project, and producing high-quality outputs for publication in
high-profile journals or conference proceedings.
The position is initially for 2 years, with possible extension up to 5
years total. We offer a highly competitive benefits package including
training and development opportunities. Washington University in St.
Louis is one of the best places for this type of interdisciplinary
research on ML and AI in telemedicine and clinical decision-making.
The position is based in St. Louis, Missouri, USA where the university
is situated in a beautiful, leafy campus near the Forest Park and many
metropolitan activities. This is a full-time position, available from
July 2019 or as soon as possible thereafter.
To Apply
To apply, please send your CV to Maureen Arends at [email protected] .
Please mention the TECTONICS project in your email.
For any questions regarding this opportunity, please feel free to contact:
- Prof. Yixin Chen ([email protected]), Department of
Computer Science and Engineering
- Prof. Michael Avidan ([email protected]) , Department
of Anesthesiology
PhD positions in machine learning at Max Planck Institute Tübingen
I am looking for prospective Ph.D. students to work with me at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. In particular, I am looking for students who have a strong mathematical background. The programming skill is a plus but is not mandatory. Our research projects will be at the intersection of kernel methods, counterfactual inference, causal inference, and learning theory (see https://krikamol.org/ for more details on my research interest). Successful candidates will also have a chance to engage in international collaborative projects. Last but not least, the successful candidates should be able to demonstrate that their motivation for the Ph.D. application is driven by a desire to solve difficult real-world problems and to push the boundary of science.
*** How to Apply ***
The applicants should already hold or are soon expected to obtain a master or equivalent degree in related areas. The application package must be a single PDF file and include
1) Curriculum vitae (CV),
2) academic transcripts (only bachelor and master degrees),
3) up to two pages in A4 of research statement describing your research experience and your research interest,
4) Names, affiliations, and email addresses of at most 3 references who can provide recommendation letters for you. Note that we will contact them directly so please make sure that the email addresses are correct.
The application package must be sent directly to [email protected]. The application will be open until we find the right candidates.
If you are at ICML19 or CVPR19, I am happy to talk in person.
*** Max Planck Institute & Tübingen ***
Max Planck Institute for Intelligent Systems (https://www.is.mpg.de/) is a world-class center for foundational research in machine learning and related areas. It is located in Tübingen, Germany (https://www.tuebingen.de/en/). Tübingen is a scenic medieval university town, cradled in what is simultaneously one of Germany’s most beautiful landscapes and one of Europe’s most economically successful areas. Most locals speak English and knowledge of German is not required to live here. The city is also not far from the Alps which is home to hundreds of high-quality ski resorts.
Best,
Krikamol
I am looking for prospective Ph.D. students to work with me at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. In particular, I am looking for students who have a strong mathematical background. The programming skill is a plus but is not mandatory. Our research projects will be at the intersection of kernel methods, counterfactual inference, causal inference, and learning theory (see https://krikamol.org/ for more details on my research interest). Successful candidates will also have a chance to engage in international collaborative projects. Last but not least, the successful candidates should be able to demonstrate that their motivation for the Ph.D. application is driven by a desire to solve difficult real-world problems and to push the boundary of science.
*** How to Apply ***
The applicants should already hold or are soon expected to obtain a master or equivalent degree in related areas. The application package must be a single PDF file and include
1) Curriculum vitae (CV),
2) academic transcripts (only bachelor and master degrees),
3) up to two pages in A4 of research statement describing your research experience and your research interest,
4) Names, affiliations, and email addresses of at most 3 references who can provide recommendation letters for you. Note that we will contact them directly so please make sure that the email addresses are correct.
The application package must be sent directly to [email protected]. The application will be open until we find the right candidates.
If you are at ICML19 or CVPR19, I am happy to talk in person.
*** Max Planck Institute & Tübingen ***
Max Planck Institute for Intelligent Systems (https://www.is.mpg.de/) is a world-class center for foundational research in machine learning and related areas. It is located in Tübingen, Germany (https://www.tuebingen.de/en/). Tübingen is a scenic medieval university town, cradled in what is simultaneously one of Germany’s most beautiful landscapes and one of Europe’s most economically successful areas. Most locals speak English and knowledge of German is not required to live here. The city is also not far from the Alps which is home to hundreds of high-quality ski resorts.
Best,
Krikamol
Max Planck Institute for Intelligent Systems
Home
Our goal is to understand the principles of <strong>Perception</strong>, <strong>Action</strong> and <strong>Learning</strong> in autonomous systems that successfully interact with complex environments and to use this understanding to design future artificially…
Berkeley using a new deep learning program to assess risk of suicide amongst veterans
Identifying patterns of risk within patients often involves a massive amount of data interpretation and algorithmic examination. New computer resources through Berkeley are today being dedicated to producing tailored algorithms for dynamic risk scores for VA patients and caregivers.
https://www.marktechpost.com/2019/04/19/berkeley-using-a-new-deep-learning-program-to-assess-risk-of-suicide-amongst-veterans/
Identifying patterns of risk within patients often involves a massive amount of data interpretation and algorithmic examination. New computer resources through Berkeley are today being dedicated to producing tailored algorithms for dynamic risk scores for VA patients and caregivers.
https://www.marktechpost.com/2019/04/19/berkeley-using-a-new-deep-learning-program-to-assess-risk-of-suicide-amongst-veterans/
MarkTechPost
Berkeley using a new deep learning program to assess risk of suicide amongst veterans
Berkeley using a new deep learning program to assess risk of suicide amongst veterans. massive amount of data interpretation and algorithmic examination.
Early Predictions of Movie Success: the Who, What, and When of Profitability
https://arxiv.org/pdf/1506.05382.pdf
https://arxiv.org/pdf/1506.05382.pdf
A Review of “Compound Probabilistic Context-Free Grammars for Grammar Induction”
https://medium.com/@ryancotterell/a-review-of-compound-probabilistic-context-free-grammars-for-grammar-induction-2cd24ad060cf
paper https://arxiv.org/pdf/1906.10225.pdf
https://medium.com/@ryancotterell/a-review-of-compound-probabilistic-context-free-grammars-for-grammar-induction-2cd24ad060cf
paper https://arxiv.org/pdf/1906.10225.pdf
Medium
A Review of “Compound Probabilistic Context-Free Grammars for Grammar Induction”
Kim et al. (2019) is one of the most exciting papers I’ve had the pleasure to read in a while. Why? It challenges long-established wisdom…
When Does Label Smoothing Help?
by Rafael Müller, Simon Kornblith, Geoffrey Hinton
https://arxiv.org/abs/1906.02629v1
by Rafael Müller, Simon Kornblith, Geoffrey Hinton
https://arxiv.org/abs/1906.02629v1
arXiv.org
When Does Label Smoothing Help?
The generalization and learning speed of a multi-class neural network can
often be significantly improved by using soft targets that are a weighted
average of the hard targets and the uniform...
often be significantly improved by using soft targets that are a weighted
average of the hard targets and the uniform...
Countdown Regression: Sharp and Calibrated Survival Predictions by Andrew Ng , Anand Avati, Tony Duan, Sharon Zhou, Kenneth Jung, Nigam H. Shah https://arxiv.org/abs/1806.08324v2
The future depends on some graduate student who is deeply suspicious of everything I have said. - Geoffrey Hinton https://t.iss.one/ArtificialIntelligenceArticles
Real-Time AR Self-Expression with Machine Learning
Augmented reality (AR) helps you do more with what you see by overlaying digital content and information on top of the physical world. For example, AR features coming to Google Maps will let you find your way with directions overlaid on top of your real world. With Playground - a creative mode in the Pixel camera -- you can use AR to see the world differently. And with the latest release of YouTube Stories and ARCore's new Augmented Faces API you can add objects like animated masks, glasses, 3D hats and more to your own selfies!
Direct Link: https://ai.googleblog.com/2019/03/real-time-ar-self-expression-with.html
Augmented reality (AR) helps you do more with what you see by overlaying digital content and information on top of the physical world. For example, AR features coming to Google Maps will let you find your way with directions overlaid on top of your real world. With Playground - a creative mode in the Pixel camera -- you can use AR to see the world differently. And with the latest release of YouTube Stories and ARCore's new Augmented Faces API you can add objects like animated masks, glasses, 3D hats and more to your own selfies!
Direct Link: https://ai.googleblog.com/2019/03/real-time-ar-self-expression-with.html
Googleblog
Real-Time AR Self-Expression with Machine Learning
[#basics][#deeplearningdevelopment]
0. Programming doubts, dont know where to ask, pls here first ?
https://stackoverflow.com/
0.1 Software versioning, software managing and production GIT
https://git-scm.com/book/en/v1/Getting-Started-Git-Basics
0.1.1 Searching for code that does something ?
https://github.com/
google for: https://github.com/repo: <term>
1. Python Programming, many references
https://www.fullstackpython.com/python-programming-language.html
A . Deep Learning Elementary Lectures by Geof Hinton
https://www.cs.toronto.edu/~hinton/coursera_lectures.html
A.1 Tensorflow Repository/**Documentation** and Issue Tracker (most popular and effective Deep Learning framework)
Issues: https://github.com/tensorflow/tensorflow/issues
Docs: https://www.tensorflow.org/api_docs/python/tf
A.2 Keras Mailing List (High Level Python Tensorflow API)
https://groups.google.com/forum/#!forum/keras-users
A.3 Tensorflow Computational Graphs Explained From Scratch
https://www.deepideas.net/deep-learning-from-scratch-i-computational-graphs/
B. Conda, One of the most impressives python virtual environment managers, essential for python development,
https://conda.io/en/latest/
B.0 Create virtual env only with the Conda manager and its dependencies: Miniconda
https://docs.conda.io/en/latest/miniconda.html
B.1 Anaconda, big Python Libs Distros
https://www.anaconda.com/
C. Conda Virtual Envs with Docker
https://medium.com/@chadlagore/conda-environments-with-docker-82cdc9d25754
0. Programming doubts, dont know where to ask, pls here first ?
https://stackoverflow.com/
0.1 Software versioning, software managing and production GIT
https://git-scm.com/book/en/v1/Getting-Started-Git-Basics
0.1.1 Searching for code that does something ?
https://github.com/
google for: https://github.com/repo: <term>
1. Python Programming, many references
https://www.fullstackpython.com/python-programming-language.html
A . Deep Learning Elementary Lectures by Geof Hinton
https://www.cs.toronto.edu/~hinton/coursera_lectures.html
A.1 Tensorflow Repository/**Documentation** and Issue Tracker (most popular and effective Deep Learning framework)
Issues: https://github.com/tensorflow/tensorflow/issues
Docs: https://www.tensorflow.org/api_docs/python/tf
A.2 Keras Mailing List (High Level Python Tensorflow API)
https://groups.google.com/forum/#!forum/keras-users
A.3 Tensorflow Computational Graphs Explained From Scratch
https://www.deepideas.net/deep-learning-from-scratch-i-computational-graphs/
B. Conda, One of the most impressives python virtual environment managers, essential for python development,
https://conda.io/en/latest/
B.0 Create virtual env only with the Conda manager and its dependencies: Miniconda
https://docs.conda.io/en/latest/miniconda.html
B.1 Anaconda, big Python Libs Distros
https://www.anaconda.com/
C. Conda Virtual Envs with Docker
https://medium.com/@chadlagore/conda-environments-with-docker-82cdc9d25754
Stack Overflow
Newest Questions
Stack Overflow | The World’s Largest Online Community for Developers
Clothing Identification Tech from CVPR 2019!
paper: [https://www.profillic.com/paper/arxiv:1901.07973](https://www.profillic.com/paper/arxiv:1901.07973?fbclid=IwAR3bIPaWZk4Plhug0SvKdQt96dR8eAPqPgK7YX4TKlMkHC8OH5vVHwUjsao)
Deepfashion 2 provides a new benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images
(The dataset contains 491K diverse images of 13 popular clothing categories from both commercial shopping stores and consumers)
paper: [https://www.profillic.com/paper/arxiv:1901.07973](https://www.profillic.com/paper/arxiv:1901.07973?fbclid=IwAR3bIPaWZk4Plhug0SvKdQt96dR8eAPqPgK7YX4TKlMkHC8OH5vVHwUjsao)
Deepfashion 2 provides a new benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images
(The dataset contains 491K diverse images of 13 popular clothing categories from both commercial shopping stores and consumers)
Profillic
Profillic: AI research & source code to supercharge your projects
Explore state-of-the-art in machine learning, AI, and robotics research. Browse papers, source code, models, and more by topics and authors. Connect with researchers and engineers working on related problems in machine learning, deep learning, natural language…
The first AI universe sim is fast and accurate—and its creators don't know how it works
https://phys.org/news/2019-06-ai-universe-sim-fast-accurateand.html
https://phys.org/news/2019-06-ai-universe-sim-fast-accurateand.html
phys.org
The first AI universe sim is fast and accurate—and its creators don't know how it works
For the first time, astrophysicists have used artificial intelligence techniques to generate complex 3-D simulations of the universe. The results are so fast, accurate and robust that even the creators ...
Applied Data Scientists / Quantitative Researchers (Stats, Machine Learning, Python/R) @ YELP London
We are looking for Applied Data Scientists / Quantitative Researchers to join our London team. Please visit the
following link for more info: https://www.yelp.com/careers/job-openings/8c288764-b1db-4b72-ac75-07b34c9f9b74
We are looking for Applied Data Scientists / Quantitative Researchers to join our London team. Please visit the
following link for more info: https://www.yelp.com/careers/job-openings/8c288764-b1db-4b72-ac75-07b34c9f9b74
Yelp
Quantitative Researcher (Stats, Machine Learning, Python/R) - Engineering - London, UK - Careers at Yelp
Join our Engineering team and help millions of people connect with local businesses on Yelp.
For those who are interested in healthcare : Machine Learning for Healthcare 2019
https://www.mlforhc.org/
https://www.mlforhc.org/
Training an AI agent to play Snake with TensorFlow 2.0.
Code by Paweł Kieliszczyk: https://github.com/pawel-kieliszczyk/snake-reinforcement-learning
#MachineLearning #ReinforcementLearning #TensorFlow
Code by Paweł Kieliszczyk: https://github.com/pawel-kieliszczyk/snake-reinforcement-learning
#MachineLearning #ReinforcementLearning #TensorFlow
GitHub
GitHub - pawel-kieliszczyk/snake-reinforcement-learning: AI (A2C agent) mastering the game of Snake with TensorFlow 2.0
AI (A2C agent) mastering the game of Snake with TensorFlow 2.0 - GitHub - pawel-kieliszczyk/snake-reinforcement-learning: AI (A2C agent) mastering the game of Snake with TensorFlow 2.0
Fast Training of Sparse Graph Neural Networks on Dense Hardware
Balog et al.: https://arxiv.org/abs/1906.11786
#artificialintelligence #neuralnetworks #machinelearning #datascience
Balog et al.: https://arxiv.org/abs/1906.11786
#artificialintelligence #neuralnetworks #machinelearning #datascience
Growing Action Spaces
Farquhar et al.: https://arxiv.org/abs/1906.12266
#deeplearning #machinelearning #reinforcementlearning
Farquhar et al.: https://arxiv.org/abs/1906.12266
#deeplearning #machinelearning #reinforcementlearning
PhD fellow in Theoretical Machine Learning
University of Copenhagen, Denmark
More Details: https://www.marktechpost.com/job/phd-fellow-in-theoretical-machine-learning/
Department of Computer Science, Faculty of Science at University of Copenhagen is offering a PhD scholarship in Theoretical Machine Learning commencing 01.10.2019 or as soon as possible thereafter.
University of Copenhagen, Denmark
More Details: https://www.marktechpost.com/job/phd-fellow-in-theoretical-machine-learning/
Department of Computer Science, Faculty of Science at University of Copenhagen is offering a PhD scholarship in Theoretical Machine Learning commencing 01.10.2019 or as soon as possible thereafter.