24 parallel-computing-"https:"-"INL---INSA-Lyon" Postdoctoral positions in United States
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
University to support outstanding research. We will foster programs in the areas of basic, translational, mechanistic, and population research. Position Summary The Phanstiel lab at UNC (http://phanstiel
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may close at any time) Job Summary The Ho lab at the University of Utah is launching an ambitious program to systematically discover, map, and therapeutically harness mitochondrial microproteins
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collaborating experimental research groups. Previous experience in computational modeling of atmospheric aerosols and parallel computing/software development is strongly desired. The term of appointment is based
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Computing Applications group in CSD has an immediate opening for a Postdoctoral Research Associate to design, develop, and deploy machine-learning and high-performance computing workflows, algorithms, and
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parallel computing. Demonstrated hands-on experience and understanding of developing scientific data management, workflows and resource management problems. Strong problem-solving and communication skills
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Oak Ridge National Laboratory, Mathematics in Computation Section Position ID: ORNL-POSTDOCTORALRESEARCHASSOCIATE5 [#27233] Position Title: Position Location: Oak Ridge, Tennessee 37831
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Oak Ridge National Laboratory, Mathematics in Computation Section Position ID: ORNL-POSTDOCTORALRESEARCHASSOCIATE3 [#27208] Position Title: Position Type: Postdoctoral Position Location: Oak Ridge
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. Experience in developing and applying advanced parametric/machine learning postprocessing techniques, producing probabilistic forecasts of hydrometeorological variables, and parallel computing. Proficiency in
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, Climate Science or a related field. Experience in earth system modeling, data assimilation, and remote sensing of land surface variables. Experience with parallel computing on high performance cluster