65 computational-complexity-"U.S"-"U.S" Postdoctoral positions at NEW YORK UNIVERSITY ABU DHABI
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machine learning. The successful applicant will participate in research involving human computation, knowledge discovery, machine learning, and data science. The position will provide the opportunity
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Description The New York University Abu Dhabi Computational Approaches to Modeling Language (CAMeL) Lab seeks to hire a post-doctoral researcher to work in any of the lab research areas, to be
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Description Quantum & Spin Lab in the Chemistry Program within the Division of Science at New York University Abu Dhabi (NYUAD), is seeking a highly motivated and skilled Post-doctoral Associate
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perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems This position
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Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in
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solutions. He/she will contribute to the development of novel concepts and proposal writing, while efficiently addressing complex challenges. Responsibilities will include writing reports, authoring
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complex sociotechnical systems Strategic learning and equilibrium-seeking algorithms in transportation networks Game-theoretic approaches to cybersecurity and security games Integration of human behavior
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systems (ITS). In particular, the successful candidate will conduct cutting-edge research in: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design
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areas: infrastructure systems modeling, emissions inventory development, air quality modeling (chemical transport models and/or reduced-complexity models), exposure assessment of airborne pollutants, and
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areas: infrastructure systems modeling, emissions inventory development, air quality modeling (chemical transport models and/or reduced-complexity models), exposure assessment of airborne pollutants, and