18 parallel-programming-"Multiple"-"Humboldt-Stiftung-Foundation"-"Simons-Foundation" Postdoctoral positions in United States
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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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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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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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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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human or monkey electrophysiology. Studies will include simultaneous recordings and stimulation from multiple, interconnected brain regions. The researcher will gain experience with the use of laminar
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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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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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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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-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