819 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" Postdoctoral positions
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, HEP-Phenomenology (hep-ph) , HEP-Theory (hep-th) , High Energy Physics , High Energy Theory , Machine Learning , Particle Physics , String Theory/Quantum Gravity/Field Theory , string-math Appl Deadline
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Requisition Id 15358 Overview: Oak Ridge National Laboratory (ORNL) is seeking an ambitious postdoctoral scientist with keen interest in artificial intelligence (AI) / machine learning (ML) and
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Consortium and host extensive supercomputing resources, including the "Cosmology Machine", some of which is part of the DiRAC national supercomputing facility. Further information may be found at http
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Skills General office suite and willingness to learn lab specific programs Supervisory Responsibilities No Required operation of university owned vehicles No Does this position require direct animal or
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(CAVs) Traffic control and signal optimisation Navigation and routing strategies Operations research and network optimisation Big data analytics and machine learning Mōu | Who You Are To be successful in
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for a qualified, creative, highly motivated postdoctoral scholar to conduct research at the intersection of robotics, controls, and machine learning. The successful candidate will help shape next
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 9 hours ago
electrical or computer engineering; and physics and electrical engineering, are also offered in the college. Post-baccalaureate certificate programs in environmental studies, applied statistics, and geographic
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, and clustering methods; Knowledge of machine learning approaches for classification and patient stratification is valued; Postdoctoral experience in the appropriate field, with research outputs ideally
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at the intersection of scientific computing and machine learning. At a high level, the project is to build neural network models of potentials that appear in Hamiltonians for time-dependent quantum systems. The postdoc
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for safety-critical bilateral teleoperation. The research will leverage a combination of passivity-based control methods and machine learning techniques to enable reliable and robust teleoperation in uncertain