18 parallel-programming-"Multiple"-"Humboldt-Stiftung-Foundation"-"Simons-Foundation" positions at Oak Ridge National Laboratory
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Theoretical Physics or a related discipline completed within the last 5 years. Experience with High Performance Computing and programming for massively parallel computers. Experience with quantum many-body
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, or similar). Experience with parallel programming frameworks (e.g., MPI, OpenMP, CUDA) and high-performance interconnects (e.g., InfiniBand). Preferred Qualifications: Familiarity with advanced storage
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learning algorithms in PyTorch. Expertise in object-oriented programming, and scripting languages. Parallel algorithm and software development using the message-passing interface (MPI), particularly as
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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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, monitoring, and tooling support across multiple clustered infrastructures, we facilitate Lab-wide R&D projects. Our HPC clusters range in scope from just a handful of nodes to over fifty-thousand cores. We
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software engineering practices. Experience with GPU computing (e.g., CUDA, HIP), parallel computing (e.g., MPI, Actor Model). Familiarity with containerization (e.g., Docker, Podman, Apptainer), networking
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leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
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developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation of results. Deliver ORNL’s mission by aligning
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, monitoring, and tooling support across multiple clustered infrastructures, we facilitate Lab-wide R&D projects. Our HPC clusters range in scope from just a handful of nodes to over fifty-thousand cores. We
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-driven techniques for the generation and exploration of complex, large-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel