179 parallel-and-distributed-computing "https:" Fellowship positions at Harvard University
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Details Title HMS - Postdoctoral Fellow in Biomedical Informatics (DBMI) School Harvard Medical School Department/Area Biomedical Informatics-Quad Position Description The Department of Biomedical
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Arnold O. Beckman Postdoctoral Fellowship in Chemical Sciences or Chemical Instrumentation Award Program Eligibility: U.S. citizenship or permanent residency required; must have no more than 18
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Health Resources in Action: Charles A. King Trust Postdoctoral Research Fellowship Program – Basic and Preclinical Science Eligibility: By the funding start date, applicants must hold a Ph.D., MD
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Department of Energy: Oak Ridge Institute for Science and Education (ORISE): Intelligence Community (IC) Postdoctoral Research Fellowship Program Eligibility: U.S. citizenship required; Ph.D
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W.E.B. Du Bois Research Institute at the Harvard University Hutchins Center: Fellowship Program Deadline Month: January Description: The Institute annually appoints scholars who conduct individual
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parallel screening platform to discover orthogonal protein binders. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing
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machine learning methods for computational materials physics and chemistry. Projects include: The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned
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Details Title HMS - Postdoctoral Fellow in Biomedical Informatics School Harvard Medical School Department/Area Position Description The Farhat Lab in the Department of Biomedical Informatics is
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Details Title Program on U.S.-Japan Relations Postdoctoral Fellow School Faculty of Arts and Sciences Department/Area Program on U.S.-Japan Relations (Weatherhead) Position Description The Program
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decarbonization, grid modernization, and the integration of distributed and flexible energy resources. Research topics may include—but are not limited to—AI-based grid operation and planning, reinforcement learning