57 cloud-computing-"https:" "https:" "https:" "https:" research jobs at Oak Ridge National Laboratory in United States
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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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the fundamental engineering understanding of gas centrifuge systems. The group leverages analytical techniques and advanced computational tools—including finite element analysis (FEA)—to evaluate and predict
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Requisition Id 15537 Overview: We are seeking a Postdoctoral Research associate in computational nuclear physics. This position focuses on nuclear theory with an emphasis on nuclear structure and
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Requisition Id 15395 Overview: The Mathematics in Computation Section at Oak Ridge National Laboratory (ORNL) invites outstanding candidates to apply for the Alston S. Householder Fellowship in
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). Knowledge of high-performance computing or cloud environments for large-scale data. Strong collaboration skills and ability to work in interdisciplinary teams. Special Requirements: Applicants cannot have
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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Director's office can be found here: https://www.ornl.gov/content/research-integrity . Basic Qualifications: A PhD in physics, chemistry, biochemistry or a related field completed within the last five years
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Requisition Id 15769 Overview: The Computational Hydrology and Atmospheric Science (CHAS) Group at Oak Ridge National Laboratory (ORNL) is seeking a highly motivated Postdoctoral Research Associate
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understanding of enrichment devices using analytical methods and computational tools such as finite element analysis (FEA). The Senior Electric Motor Researcher will provide research and development (R&D
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liquids, frustrated magnetism, excitonic magnets, and strongly correlated electron systems. You will work closely with theorists, experimentalists, and computer scientists to build robust, scalable