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Mathematics, or a related field, awarded within the last five years Programming experience in one or more of Python, C++, Fortran, or Julia Knowledge of high-performance and parallel computing Experience
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sequence programming (e.g., IDEA/ICE) and contemporary image reconstruction techniques (e.g., compressed sensing, parallel imaging, model-based or deep learning reconstructions). Knowledge of radial data
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sequence programming (e.g., IDEA/ICE) and contemporary image reconstruction techniques (e.g., compressed sensing, parallel imaging, model-based or deep learning reconstructions). Knowledge of radial data
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, to analyze performance, improve portability and reliability, and bring new workflow capabilities to thousands of users across DOE Office of Science programs. What You Will Do: Contribute to one or more NESAP
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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
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partners at NVIDIA and Dell, to analyze performance, improve portability and reliability, and bring new workflow capabilities to thousands of users across DOE Office of Science programs. What You Will Do
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with environment, safety, health and quality program requirements. Maintain strong dedication to the implementation and perpetuation of values and ethics. Deliver ORNL’s mission by aligning behaviors
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dynamics (DNS, LES, or RANS) and/or high-performance computing (MPI, GPU, or parallel solvers), as demonstrated by application materials. Evidence of peer-reviewed publications in fluid dynamics, turbulence
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multiphase flow in porous media. 80% - Applying numerical and analytical infiltration models to quantify groundwater recharge potential under varying hydrogeologic conditions. In parallel, the researcher will
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computational fluid dynamics (DNS, LES, or RANS) and/or high-performance computing (MPI, GPU, or parallel solvers), as demonstrated by application materials. Evidence of peer-reviewed publications in fluid