127 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" research jobs at NEW YORK UNIVERSITY ABU DHABI
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scientific capacity in the region. The candidate will also lead NYUAD’s annual Southeast Asia Learning Exchange, an immersive week long program that brings regional researchers to Abu Dhabi for advanced
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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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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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, and machine learning experience; and (c) some research publication experience. Knowledge of Arabic language is preferred, but not required. Previous work on Arabic NLP is preferred but not required
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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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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
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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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or willingness to learn quickly. Publications, thesis work, or demonstrable projects in computer vision, multi-modal ML, digital twins or biomedical ML. Familiarity with uncertainty quantification and model
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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