180 assistant-professor-computer-science-data-"https:"-"https:"-"https:"-"https:"-"UCL" positions in United Arab Emirates
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3 Mar 2026 Job Information Organisation/Company NEW YORK UNIVERSITY ABU DHABI Research Field Economics Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application Deadline
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the rank of Research Assistant (with BS or MS). A strong preference is for individuals with (a) computer science or computer engineering degrees including previous experience in natural language processing
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undergraduate program in the Arts, Sciences, Social Sciences, Humanities, and Engineering. NYU Abu Dhabi, NYU New York, and NYU Shanghai, form the backbone of NYU’s global network university, an interconnected
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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 York, and NYU Shanghai, form
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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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interdisciplinary involving behavioral economics, psychology, neuroscience, computer science applied to the transport domain. Responsibilities of the position include building experiments to understand user’s
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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 York, and NYU Shanghai, form
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PhD degree in Mathematics, statistics or theoretical computer science. The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be
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Engineering, Computer Science, Computer Engineering, Information Systems, or a closely related field. Technical Expertise in one or more of the following areas: Software architecture and design patterns
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Postdoctoral Associate under the supervision of Professor Hanan Salam to work on the development of frameworks, tools, and theoretical foundations for bias detection and mitigation in AI & data science, with a