200 computer-science-intern-"https:"-"https:"-"https:"-"https:" positions in United Arab Emirates
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Description Mubadala Arabian Center for Climate and Environmental Sciences (ACCESS) at New York University
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the position is filled. About NYUAD: NYU Abu Dhabi is a degree-granting research university with a fully integrated liberal arts and science undergraduate program in the Arts, Sciences, Social Sciences
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to communicate research findings to the global scientific community. A candidate with a Master’s degree is preferred; however, the minimum requirement is a Bachelor’s degree in physics, computer science, or a
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27 Jan 2026 Job Information Organisation/Company NEW YORK UNIVERSITY ABU DHABI Research Field Engineering Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application
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infrastructure inspection and vibration monitoring Successful candidates must hold a PhD degree in Civil, Structural, Mechanical, or Material Engineering. Other related field such as Computer Science, Nuclear
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Apr 2026 - 00:00 (UTC) Country United Arab Emirates Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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primarily research on Reinforcement Learning, and/or Optimal Control, and/or Model Predictive Control. RISC invites qualified applicants in the areas of electrical, computer, or mechanical engineering, or
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a degree-granting research university with a fully integrated liberal arts and science undergraduate program in the Arts, Sciences, Social Sciences, Humanities, and Engineering. NYU Abu Dhabi, NYU New
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liberal arts and sciences education. The university supports groundbreaking research that pushes the boundaries of knowledge and responds to vital global and local issues with powerful interdisciplinary
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Science at MBZUAI focuses on the rigorous statistical and probabilistic foundations of machine learning and data science. We emphasize computational methods for large-scale data and scalable inference