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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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Research / Post-Doctoral Associate in the Division of Science Computer Science, Dr. Djellel Difallah
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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of concrete. To develop structural-health-monitoring networks specifically directed toward the oil and gas industry. To develop novel self-healing cementitious materials through chemical and/or bio
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, cardiovascular, and neurologic diseases. These projects entail computational modeling, device design and manufacturing, optimization of chemical, mechanical, and electrical characteristics, and preclinical
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collaborations with Cleveland Clinic Abu Dhabi to develop and test the “phenotypic fingerprint” method. This approach is inspired by large ongoing studies including the UK Biobank and the Human Connectome Project
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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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September 2025. The successful candidate must have previous research experience (computational and experimental) in the broad area of Nonlinear Mechanics. Applicants must have received a Ph.D. in Mechanical
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Engineering, Computer Science, Applied Mathematics, or related fields Strong background in control systems, machine learning, and scientific computing Programming proficiency and experience with simulation
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modeling in smart mobility systems Required Qualifications: The requirements for the applicants include: Ph.D. in Electrical Engineering, Computer Science, Operations Research, Applied Mathematics
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
performance and ground risks in variable and uncertain geologies. The researcher will be embedded in a team that spans infrastructure resilience, computational geomechanics, and data-driven risk evaluation. The