246 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions in United Arab Emirates
Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
/Females/Vet/Disabled/SexualOrientation/Gender Identity Employer UAE Nationals are encouraged to apply Where to apply Website https://www.timeshighereducation.com/unijobs/listing/408278/post-doctoral-assoc
-
the Job related to staff position within a Research Infrastructure? No Offer Description Description The Deep Learning laboratory in the Division of Science, New York University Abu Dhabi, seeks
-
to apply Website https://www.timeshighereducation.com/unijobs/listing/408037/post-doctoral-assoc… Requirements Additional Information Work Location(s) Number of offers available1Company/InstituteNEW YORK
-
soft robot-assisted simulations in the areas of brain machine interaction, wearable haptics, and rehabilitation. The successful applicant will have the following technical experience in: PhD degree in
-
Computer Vision, Image Processing, and Deep Learning methods. Experience with modern computer vision frameworks and tools (e.g., OpenCV, PyTorch, TensorFlow). Strong commitment to excellence in teaching and
-
cover letter, curriculum vitae with full publication list, statement of research interests, at least two reference letters and a transcript, all in PDF format. Please visit our website at https
-
of this project is to add support for automatic code optimization in Tiramisu. In particular, we want to use machine learning/deep learning to achieve this. Currently, a basic automatic optimization module
-
developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
-
attending social science conferences, is expected and supported. About NYU Abu Dhabi https://nyuad.nyu.edu/en/ NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to
-
research team working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI