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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
Description The Center for Interdisciplinary Data Science and Artificial Intelligence (CIDSAI) at NYU Abu Dhabi seeks to recruit a motivated and passionate post-doctoral associate to work under the
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: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine learning and artificial intelligence models focused
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under hardware constraints, beamforming techniques for FR3 and THz bands, reconfigurable intelligent surfaces (RIS), and integrated sensing and communications (ISAC). The research methodology will involve
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such as artificial intelligence applications in geotechnics, geoenvironmental engineering, geohazards risk assessment, or energy geotechnics will be considered an asset. Research Project: The successful
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those studying human behavior and artificial intelligence are especially encouraged to apply. The successful candidate is expected to: Conduct and publish research in leading journals in social science or
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, artificial intelligence, computer vision, robotics, UAVs, etc. is a plus. Other preferred qualifications include: expertise in programming and coding (preferably using Python and C++) and GUI development
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
Dhabi https://nyuad.nyu.edu/en/ NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher
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paradigms, including continuous aperture MIMO, pre-optimized MIMO arrays, flexible intelligent metasurfaces, and tri-hybrid MIMO systems, with a particular emphasis on near-field propagation regimes relevant
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software tools The development and validation of machine learning and artificial intelligence models focused on representing the structural response Physical experimental testing for structural and
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: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine learning and artificial intelligence models focused