74 parallel-computing-numerical-methods Postdoctoral research jobs at Oak Ridge National Laboratory
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Requisition Id 16337 Overview: Interested in taking your scientific computing skills to the next level? We are seeking a research scientist to work in a world-class research group focused
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research and development in the areas of gauge field generation, linear and eigen-solvers, or novel analysis methods. This position will reside in the Advanced Computing for Nuclear, Particle and
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. Design and implement distributed and parallel approaches that efficiently leverage large-scale computing resources, including heterogeneous CPU/GPU systems, along with the possibility of working with
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HPC research within past five years. Preferred Qualifications: The ability to work independently and develop and deploy methods at scale. Experience in high-performance computing and software
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Requisition Id 16562 Overview: The Analytics and AI Methods at Scale (AAIMS) group at the National Center of Computational Science (NCCS) at the Oak Ridge National Laboratory (ORNL) is seeking
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candidate will join the Multiscale Materials (MsM) group within the Advanced Computing Methods for Physical Sciences Section in CSED. The MsM group is dedicated to delivering multiscale, multi-fidelity
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methods. Additionally, you will develop/refine finite element and numerical analysis models to portray shear strength response as a function of temperature, and to attempt to ultimately reconcile those
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experience in hydrological or Earth system modeling, with emphasis on process understanding and prediction. Strong background in computational sciences, including numerical methods, high-performance computing
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. Experience with heterogeneous and parallel computing technologies, programming models, or accelerators, including CPUs, GPUs, FPGAs, and emerging computing technologies. Familiarity with quantum software
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Computing Methods for Physical Sciences Section in CSED. The MsM group is focused on delivering multiscale, multi-fidelity computational models and systems using algorithms and analytics for materials and