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301.975.8582 Michael Garth Huber michael.huber@nist.gov 301 975 5641 Description This program explores complementary aspects of atom and neutron interferometry with particular emphasis on their interplay with
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/C++, Fortran, and/or Python Proven experience with multiple parallel programming paradigms, including but not limited to; MPI, OpenMP, and CUDA (Compute Unified Device Architecture) Experience in a
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Your tasks: Developing optimization algorithms for massively parallel hardware architectures such as AI
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) Established Researcher (R3) Country Italy Application Deadline 22 Jan 2026 - 12:00 (UTC) Type of Contract To be defined Job Status Not Applicable Is the job funded through the EU Research Framework Programme
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We are looking for highly motivated early-career postdoctoral scientists willing to conduct independent research in computational biology at Nantes University in France. Nantes University has
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required. Five years of experience in an academic setting, preferably in an academic program, department, or school. PREFERRED QUALIFICATIONS: PhD or equivalent/parallel degree required. Seven years
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About us Recently re-founded, the Department of Engineering is rapidly expanding into a world-class research and teaching department. Research currently focuses on computational engineering
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 5 hours ago
approaches include MHD, Vlasov, and hybrid codes run on computers ranging from PCs to massively parallel computers, while analytical work involves linear and nonlinear instability theories. Location: Goddard
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ecomorphological outcomes significantly parallel. As a next step, it is vital to dig more deeply into the molecular mechanisms driving these patterns. This project will examine replicate divergences into specialist
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(fastest execution) for a given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations