Postdoc opening at KAUST Vision-CAIR Group starting Fall 2020-Spring 2021
Vision-CAIR group at KAUST (https://cemse.kaust.edu.sa/vision-cair) is inviting top postdoctoral researchers with experience with computer vision/ AI/ machine learning starting Fall 2020/Spring 2021. Posdoc researchers at the Vision-CAIR group are expected to develop principled understanding and computational approaches in the following research themes: A) learning efficiency /computational creativity (zero/few-shot/long-tail learning of visual tasks. This also includes efficient generative models that are capable of generating and understanding unseen art/fashion/3d design ) B) continual learning (e.g. alleviating catastrophic forgetting in various learning settings including recognition RL), C) vision and language (this overlaps with the former themes as we integrate 2D/3D vision with language in most of the work different these themes). This is a video, about imagination inspired AI where I describe what is Imagination Inspired AI which relates to A and C themes, part of the research we do at Vision-CAIR group among other topics https://www.youtube.com/watch?v=Z1dytXfbFkM. This is also a presentation that covers continual learning (theme: B) methods that we have worked on https://www.dropbox.com/s/sdtbmptu7a2chks/deepcontinuallearning.pdf.
Scope
You will be part of the Visual Computing Center at KAUST, according to csranking.org among the top 10 world-wide in Computer Vision & Graphics. @ArtificialIntelligenceArticles
Excellent total compensation, including accommodation, family health benefits, moving expenses, and a substantial tax-free annual salary. Tuition fees, travel to conferences, and research equipment will be covered.
Mentoring and collaborating with KAUST grad students and visiting students/researchers
You will have access to world-class compute equipment of close to a thousand GPU.
Housing Expenses is completely or at least partially covered till a limit.
KAUST community is very diverse with more than 100 nationalities from all over the globe and school is located in the beautiful city of Thuwal on the shores of the red sea.
@ArtificialIntelligenceArticles
Requirements
a PhD degree with excellent academic credentials
relevant research skills and experience in computer vision, machine/deep learning, or optimization, demonstrated by high quality publications
good verbal communication (for daily interaction)
good written communication (for daily interaction)
clarity of thought / systematic thinking
attention to detail
good professional writing skills (e.g., able to write a reasonable abstract or a paper draft)
reliability / accountability
good coding skills
If you are interested, please feel free to send me an email with your CV with your full list of publications ([email protected] , [email protected])
Best,
Mohamed Elhoseiny
Assistant Professor of Computer Science, KAUST
Visiting Faculty, Stanford University, Computer Science Department.
https://www.mohamed-elhoseiny.com/ (personal website)
https://cemse.kaust.edu.sa/vision-cair (group website)
Vision-CAIR group at KAUST (https://cemse.kaust.edu.sa/vision-cair) is inviting top postdoctoral researchers with experience with computer vision/ AI/ machine learning starting Fall 2020/Spring 2021. Posdoc researchers at the Vision-CAIR group are expected to develop principled understanding and computational approaches in the following research themes: A) learning efficiency /computational creativity (zero/few-shot/long-tail learning of visual tasks. This also includes efficient generative models that are capable of generating and understanding unseen art/fashion/3d design ) B) continual learning (e.g. alleviating catastrophic forgetting in various learning settings including recognition RL), C) vision and language (this overlaps with the former themes as we integrate 2D/3D vision with language in most of the work different these themes). This is a video, about imagination inspired AI where I describe what is Imagination Inspired AI which relates to A and C themes, part of the research we do at Vision-CAIR group among other topics https://www.youtube.com/watch?v=Z1dytXfbFkM. This is also a presentation that covers continual learning (theme: B) methods that we have worked on https://www.dropbox.com/s/sdtbmptu7a2chks/deepcontinuallearning.pdf.
Scope
You will be part of the Visual Computing Center at KAUST, according to csranking.org among the top 10 world-wide in Computer Vision & Graphics. @ArtificialIntelligenceArticles
Excellent total compensation, including accommodation, family health benefits, moving expenses, and a substantial tax-free annual salary. Tuition fees, travel to conferences, and research equipment will be covered.
Mentoring and collaborating with KAUST grad students and visiting students/researchers
You will have access to world-class compute equipment of close to a thousand GPU.
Housing Expenses is completely or at least partially covered till a limit.
KAUST community is very diverse with more than 100 nationalities from all over the globe and school is located in the beautiful city of Thuwal on the shores of the red sea.
@ArtificialIntelligenceArticles
Requirements
a PhD degree with excellent academic credentials
relevant research skills and experience in computer vision, machine/deep learning, or optimization, demonstrated by high quality publications
good verbal communication (for daily interaction)
good written communication (for daily interaction)
clarity of thought / systematic thinking
attention to detail
good professional writing skills (e.g., able to write a reasonable abstract or a paper draft)
reliability / accountability
good coding skills
If you are interested, please feel free to send me an email with your CV with your full list of publications ([email protected] , [email protected])
Best,
Mohamed Elhoseiny
Assistant Professor of Computer Science, KAUST
Visiting Faculty, Stanford University, Computer Science Department.
https://www.mohamed-elhoseiny.com/ (personal website)
https://cemse.kaust.edu.sa/vision-cair (group website)
YouTube
Imagination Inspired AI
"Imagination Inspired AI Research at Vision-CAIR group led by Prof. Mohamed Elhoseiny
https://cemse.kaust.edu.sa/vision-cair"
https://cemse.kaust.edu.sa/vision-cair"
ML and NLP Postdocs at Northwestern University Medical School (working with >8 million patient data)
We are recruiting multiple postdoctoral fellows at Northwestern University’s Feinberg School of Medicine. The postdoctoral fellow is expected to conduct research under guidance from Dr. Yuan Luo, Associate Professor and Chief AI Scientist, Northwestern University Clinical and Translational Sciences Institute. Our group website: https://labs.feinberg.northwestern.edu/lyg/. The fellow will also have the opportunities to work closely with top-notch clinicians from Northwestern Memorial Hospital, and clinical, genetic and imaging data of >8 million patients from Northwestern Medicine Enterprise Data Warehouse.
The successful candidate will have PhD in EECS, Biomedical Informatics, IEMS, Physics or related fields with solid programming skills. Experiences in one or more of the following areas are desirable: Machine Learning (ML) and/or Natural Language Processing (NLP) and/or time series analysis and/or -omic analysis. The candidate should demonstrate good communication skills and ability to work in a collaborative environment, to coordinate and supervise part of the research project.
We offer a competitive salary and an initial appointment of 12 months, starting 2019/2020. Extension of the postdoctoral position for up to 3 years is possible. Northwestern University is an exceptional research institution that has a world-class medical school and is an emerging hub in biomedical AI; our department is located in downtown Chicago, one of the most vibrant cities in the US. Be part of a prestigious institution that offers great benefits, and enjoy our lakefront working environment.
Please send your application to Yuan Luo <[email protected]>, which should include:
- Curriculum vitae
- List of publications (attach a copy of one of your strongest papers)
- Contact details for 2 to 3 references
Northwestern University is an Equal Opportunity/Affirmative Action Employer.
We are recruiting multiple postdoctoral fellows at Northwestern University’s Feinberg School of Medicine. The postdoctoral fellow is expected to conduct research under guidance from Dr. Yuan Luo, Associate Professor and Chief AI Scientist, Northwestern University Clinical and Translational Sciences Institute. Our group website: https://labs.feinberg.northwestern.edu/lyg/. The fellow will also have the opportunities to work closely with top-notch clinicians from Northwestern Memorial Hospital, and clinical, genetic and imaging data of >8 million patients from Northwestern Medicine Enterprise Data Warehouse.
The successful candidate will have PhD in EECS, Biomedical Informatics, IEMS, Physics or related fields with solid programming skills. Experiences in one or more of the following areas are desirable: Machine Learning (ML) and/or Natural Language Processing (NLP) and/or time series analysis and/or -omic analysis. The candidate should demonstrate good communication skills and ability to work in a collaborative environment, to coordinate and supervise part of the research project.
We offer a competitive salary and an initial appointment of 12 months, starting 2019/2020. Extension of the postdoctoral position for up to 3 years is possible. Northwestern University is an exceptional research institution that has a world-class medical school and is an emerging hub in biomedical AI; our department is located in downtown Chicago, one of the most vibrant cities in the US. Be part of a prestigious institution that offers great benefits, and enjoy our lakefront working environment.
Please send your application to Yuan Luo <[email protected]>, which should include:
- Curriculum vitae
- List of publications (attach a copy of one of your strongest papers)
- Contact details for 2 to 3 references
Northwestern University is an Equal Opportunity/Affirmative Action Employer.
Free Online Courses | Harvard University
Free Online Courses. Digital Media. Music. Business. General. Business Development. Business Development. Computer Science. General. Computer Science. Artificial Intelligence. Data Science. General. Data Science. General. Education. Teacher Development. General. Healthcare. Healthcare. Humanities.
Click on the given link below:
1. Computer Science: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=3&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
2. Data Science: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=84&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
3. Programming: https://online-learning.harvard.edu/catalog?keywords=&subject%5B1%5D=100&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
4. Business: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=2&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
5. Arts & Design: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=1&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
6. Education and Teaching: https://online-learning.harvard.edu/catalog?keywords=&subject%5B1%5D=5&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
7. Health & Medicine: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=10&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
8. Humanities: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=8&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
9. Mathematics: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=9&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
10: Science: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=11&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
11: Social Science: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=13&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
#HARVARD_UNIVERSITY_FREE_ONLINE_COURSE #COMPUTER_SCIENCE #DATA_SCIENCE #PROGRAMMING #BUSINESS #ARTS_AND_DESIGN #EDUCATION_AND_TEACHING #HEALTH_AND_MEDICINE #HUMANITIES #MATHEMATICS #SCIENCE #SOCIAL_SCIENCE
Free Online Courses. Digital Media. Music. Business. General. Business Development. Business Development. Computer Science. General. Computer Science. Artificial Intelligence. Data Science. General. Data Science. General. Education. Teacher Development. General. Healthcare. Healthcare. Humanities.
Click on the given link below:
1. Computer Science: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=3&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
2. Data Science: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=84&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
3. Programming: https://online-learning.harvard.edu/catalog?keywords=&subject%5B1%5D=100&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
4. Business: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=2&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
5. Arts & Design: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=1&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
6. Education and Teaching: https://online-learning.harvard.edu/catalog?keywords=&subject%5B1%5D=5&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
7. Health & Medicine: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=10&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
8. Humanities: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=8&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
9. Mathematics: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=9&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
10: Science: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=11&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
11: Social Science: https://online-learning.harvard.edu/catalog?keywords=&subject%5B%5D=13&max_price=&start_date_range%5Bmin%5D%5Bdate%5D=&start_date_range%5Bmax%5D%5Bdate%5D=
#HARVARD_UNIVERSITY_FREE_ONLINE_COURSE #COMPUTER_SCIENCE #DATA_SCIENCE #PROGRAMMING #BUSINESS #ARTS_AND_DESIGN #EDUCATION_AND_TEACHING #HEALTH_AND_MEDICINE #HUMANITIES #MATHEMATICS #SCIENCE #SOCIAL_SCIENCE
Harvard Online Courses
Online Courses
Browse the latest online courses from Harvard University, including "Nonprofit Financial Stewardship Webinar: Introduction to Accounting and Financial Statements" and "Blackburn Course in Obesity
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment
Nanni et al.: https://arxiv.org/abs/2004.05222
#Covid19Response #Data #Society #SocialNetworks
@ArtificialIntelligenceArticles
Nanni et al.: https://arxiv.org/abs/2004.05222
#Covid19Response #Data #Society #SocialNetworks
@ArtificialIntelligenceArticles
List of COVID-19 Resources for Machine Learning and Data Science Research
@ArtificialIntelligenceArticles
https://www.marktechpost.com/2020/04/12/list-of-covid-19-resources-for-machine-learning-and-data-science-research/
@ArtificialIntelligenceArticles
https://www.marktechpost.com/2020/04/12/list-of-covid-19-resources-for-machine-learning-and-data-science-research/
MarkTechPost
List of COVID-19 Resources for Machine Learning and Data Science Research
Here is a list of COVID-19 tools and public datasets which could be really helpful in understanding the disease (COVID-19) and performing data driven research. 1. California COVID-19 Hospital Data and Case Statistics Resource link: https://data.chhs.ca.g…
A new path for describing the fundamental theory of physics, by Wolfram et al. The end point could be one of mankind's largest intellectual accomplishments.
1) Explanation by Professor Wolfram (Inventor of Wolfram Language, and recipient of MacArthur Grant at only age 21):
https://writings.stephenwolfram.com/2020/04/finally-we-may-have-a-path-to-the-fundamental-theory-of-physics-and-its-beautiful/
2) The Wolfram Fundamental Physics Project page:
https://www.wolframphysics.org/
3) Registry of Notable Universe Models (one of which may turn out to represent our universe):
https://www.wolframphysics.org/universes/
1) Explanation by Professor Wolfram (Inventor of Wolfram Language, and recipient of MacArthur Grant at only age 21):
https://writings.stephenwolfram.com/2020/04/finally-we-may-have-a-path-to-the-fundamental-theory-of-physics-and-its-beautiful/
2) The Wolfram Fundamental Physics Project page:
https://www.wolframphysics.org/
3) Registry of Notable Universe Models (one of which may turn out to represent our universe):
https://www.wolframphysics.org/universes/
Stephenwolfram
Finally We May Have a Path to the Fundamental Theory of Physics… and It’s Beautiful—Stephen Wolfram Writings
How does our universe work? Scientist Stephen Wolfram opens up his ongoing Wolfram Physics Project to a global effort. His team will livestream work in progress, post working materials, release software tools and hold educational programs.
COVID-19 Anti-Viral Cure Using Deep Reinforcement Learning
Ifiok Charles : https://github.com/Ifiokcharles/COVID-19-Anti-viral-cure-using-deep-reinforcement-learning
#Covid19 #DeepLearning #ReinforcementLearning
Ifiok Charles : https://github.com/Ifiokcharles/COVID-19-Anti-viral-cure-using-deep-reinforcement-learning
#Covid19 #DeepLearning #ReinforcementLearning
GitHub
GitHub - Ifiokcharles/COVID-19-Anti-viral-cure-using-deep-reinforcement-learning
Contribute to Ifiokcharles/COVID-19-Anti-viral-cure-using-deep-reinforcement-learning development by creating an account on GitHub.
Building a Powerful DQN in TensorFlow 2.0 (explanation & tutorial)
Sebastian Theiler: https://medium.com/analytics-vidhya/building-a-powerful-dqn-in-tensorflow-2-0-explanation-tutorial-d48ea8f3177a
#ReinforcementLearning #MachineLearning #Python #TensorFlow
Sebastian Theiler: https://medium.com/analytics-vidhya/building-a-powerful-dqn-in-tensorflow-2-0-explanation-tutorial-d48ea8f3177a
#ReinforcementLearning #MachineLearning #Python #TensorFlow
Medium
Building a Powerful DQN in TensorFlow 2.0 (explanation & tutorial)
And scoring 350+ by implementing extensions such as double dueling DQN and prioritized experience replay
Monte Carlo Sampling using Langevin Dynamics
I wrote an article on the basics of Langevin Monte Carlo techniques. Please let me know if you find any errors.
Code: https://github.com/abdulfatir/langevin-monte-carlo
Visualization: https://www.youtube.com/watch?v=cVn0kru3hL8
I hope it's helpful for someone. :)
https://abdulfatir.com/Langevin-Monte-Carlo/
I wrote an article on the basics of Langevin Monte Carlo techniques. Please let me know if you find any errors.
Code: https://github.com/abdulfatir/langevin-monte-carlo
Visualization: https://www.youtube.com/watch?v=cVn0kru3hL8
I hope it's helpful for someone. :)
https://abdulfatir.com/Langevin-Monte-Carlo/
GitHub
GitHub - abdulfatir/langevin-monte-carlo: A simple pytorch implementation of Langevin Monte Carlo algorithms.
A simple pytorch implementation of Langevin Monte Carlo algorithms. - abdulfatir/langevin-monte-carlo
Google’s Dataset Search
"Dataset Search has indexed almost 25 million of these datasets, giving you a single place to search for datasets & find links to where the data is.” — Natasha Noy
https://datasetsearch.research.google.com
#ArtificialIntelligence #Datasets #MachineLearning
"Dataset Search has indexed almost 25 million of these datasets, giving you a single place to search for datasets & find links to where the data is.” — Natasha Noy
https://datasetsearch.research.google.com
#ArtificialIntelligence #Datasets #MachineLearning