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The National Energy Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivated Postdoctoral Fellow — HPC Scientific Workflows (NESAP @ NERSC) postdoctoral fellow to
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applicability to new domains, including HPC systems, in order to identify different usage alternatives (e.g., user-space execution). It also intends to design and develop new features that extend and improve
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developing an efficient storage solution for AI applications deployed at HPC centers. In detail, the work will focus on the development of a storage solution that optimizes the persistence of checkpoints of AI
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, and analysis of large, diverse datasets that benefit from high-performance computing (HPC) clusters. The objective of these fellowships is to facilitate cross-disciplinary, cross-location research
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on Phase Field modelling and High-Performance Computing (HPC) for geophysical applications. The Asian School of the Environment (ASE) at Nanyang Technological University is an interdisciplinary school
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supercomputers in Europe, was a founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe), and is now hosting entity for EuroHPC JU, the Joint
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to complex, multimodal data. Hands-on experience with high-performance computing (HPC) or cloud-based big-data pipelines. Experience with large-scale human genomic, omics, or brain imaging datasets. Strong
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workflows targeting NERSC HPC resources, edge resources, and the DOE ESnet network. Develop and apply advanced workflow capabilities to improve performance, portability, and productivity of scientific
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; or Experience with high-fidelity solvers, e.g. SU2, OpenFoam, StarCCM+, Fluent; Proficiency in programming, e.g. Python, Matlab, C; Experience utilizing high-performance computing (HPC) to parallelize workflows
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development new functionalities associated with eBPF technology. Specifically, it aims to explore its applicability to new domains (e.g., observability in HPC systems) as well as the design and development