121 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" Postdoctoral research jobs at NEW YORK UNIVERSITY ABU DHABI in United Arab Emirates
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scholarly thought, advanced research, knowledge creation, and sharing, through its academic, research, and creative activities. UAE Nationals are encouraged to apply. Where to apply Website https
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Description The Robot Learning & Control Lab (REAL Lab) at NYU Abu Dhabi is seeking an outstanding Post-Doctoral Associate to contribute to cutting-edge research in robot intelligence, machine
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. Applications will be accepted immediately and candidates will be considered until the position is filled. About NYU Abu Dhabi https://nyuad.nyu.edu/en/ NYU Abu Dhabi is the first comprehensive liberal arts and
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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fostering academic excellence in learning, research, and teaching. UAE Nationals are encouraged to apply. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/406710/post-doctoral-assoc
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, seeks a Post-Doctoral Associate or a Research Associate to join a lab focused on applied machine learning. The successful applicant will participate in research involving human computation, knowledge
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the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations
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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
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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
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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