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)-POSTDOC [#31861] Position Title: Position Type: Postdoctoral Position Location: Bellaterra, Catalonia 08193, Spain [map ] Subject Area: Physics / Medical Physics Appl Deadline: none (posted 2026/03/24 04
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, machine learning, and optimization, broadly defined. Applicants working at the intersection of these areas, especially those applying theoretical and computational methods to problems in management science
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-changing technologies. Life-changing careers. Learn more about Sandia at: https://www.sandia.gov *These benefits vary by job classification. What Your Job Will Be Like: We are seeking a Postdoctoral
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 hour ago
solid academic background in polymer synthesis and electrochemistry. The candidates should be self-motivated to explore new areas of studies including AI related and machine learning fields, have evidence
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of optimization and machine learning. • Knowledge of reinforcement learning and black box optimization would be a plus. Skills • The candidate must be comfortable with algorithmic development using
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 25-Mar-26 Location: Brooklyn, NY Categories: Academic/Faculty Internal Number: 183730 POSTDOCTORAL ASSOCIATE New York
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appointment is for one year, renewable for a second year pending satisfactory performance and availability of funding. Research topics of interest include numerical methods for scientific machine learning and
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Summary The Silver lab at Duke University School of Medicine seeks a highly motivated fully funded postdoctoral research fellow to join our lab. Our lab investigates mechanisms by which the brain is
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materials using statistical mechanics, molecular simulations, and machine learning. Expectations Candidates will be responsible for: Developing multi-scale modeling methods for polymeric materials, using
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities