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—or have completed all PhD requirements before starting—in computer science, information science, data science, computational social science, electrical or computer engineering, or a closely related
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before starting—in computer science, electrical or computer engineering, information science, or a closely related discipline. Less than 5 years post receiving the Doctoral degree. Meet the mandatory
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distributed decision-making. Applicants must have a PhD in Electrical Engineering, Mechanical Engineering, Computer Engineering, Applied Mathematics, Mathematics, or a closely related discipline, and are within
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. Qualifications Essential Qualifications: PhD in computer science/engineering with expertise in a security or privacy research topic. Less than 5 years post-receiving the Doctoral degree. Excellent analytic, design
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collection, data engineering, statistical modeling, or computational text and image analysis; Machine learning, natural-language processing, large language models, or evaluation and auditing of AI and online
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills include: Strong foundation in one of the following areas: Machine Learning / Information Retrieval
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Post-Doctoral Associate in the Division of Engineering (Mechanical Engineering) - Dr. Mohammed Daqaq
and experimental, in the broad field of nonlinear mechanics. Preference will be given to applicants with expertise in machine learning, wave propagation, metamaterials, and/or fluid–structure
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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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Description The Center for Artificial Intelligence and Robotics (CAIR) at NYU Abu Dhabi invites qualified applicants with a doctorate degree in the areas of electrical or computer engineering or
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM