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. The project activities will involve the development of the theory and implementation of the advanced mechanics and numerical models as well as constitutive model calibration and validation based on physical
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workflows in complex organizational settings. Qualifications: Applicants must have a PhD in Computer Science or related field. Experience in one or more ML domains, such as deep learning, reinforcement
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, mathematics, and innovation. Candidates must hold (or be close to completing) a Ph.D. in Applied Mathematics, Electrical or Mechanical Engineering, Physics and Applied Physics or a related field. Working in a
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. Moreover, the post-doctoral associate will have access to the well-equipped core research facilities of NYUAD. Applicants must hold a PhD or equivalent degree in solid-state chemistry, physics, electrical
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must have a PhD in Robotics, Control Theory, Mechanical or Electrical Engineering, Applied Mathematics, or a closely related field, with a strong focus on robot control, machine learning, and
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and data science, the impact of cybersecurity on transportation systems, and more. Applicants must have received a PhD in engineering, computer science, urban science, or a related field. Experience in
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apply. A PhD dissertation or research papers that demonstrate a strong interest and research focus in any of risk analysis or minimization, robust optimization, deep learning for systems, probabilistic
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, specifically aimed at applications in the oil and gas sector. Moreover, the candidate will have access to the well-equipped core research facilities of NYUAD. Applicants must hold a PhD or equivalent degree in