119 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Postdoctoral research jobs at NEW YORK UNIVERSITY ABU DHABI in United Arab Emirates
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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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to contribute to cutting-edge research in robot intelligence, machine learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms
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Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a
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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/408031/post-doctoral-assoc
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, samreen.malik@nyu.edu , rs8561@nyu.edu or wha221@nyu.edu . 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 be
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with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running natural language processing and machine learning workflows; (3) experimental design
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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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. 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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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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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 systems