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scientific computing, control theory, data science, data driven methods, discrete mathematics, graph algorithms, high-performance computing, integral equations and nonlocal models, linear and multilinear
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Ridge National Laboratory (ORNL) is seeking a staff fellow with expertise in machine learning and high performance computing to help develop high-fidelity computational tools that are used for large-scale
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High Performance Computing (HPC) group to apply leadership expertise coupled with technical proficiency to forge the pathway for this new group. This position combines advanced technical skills with
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high performance computing or related environments. A combination of equivalent education and experience may be considered. Strong understanding of IT infrastructure, including compute, storage
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machine learning and high performance computing to help develop high-fidelity computational tools that are used for large-scale, physics-based simulations of fusion energy systems in partnership with
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operations of the UT-Battelle Operations Committee. Represent ORNL in high-level discussions with DOE-SC and peer laboratories on institutional performance matters. Facilitate executive forums and strategic
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highly qualified individual to play a key role in improving the security, performance, and reliability of the NCCS computing environments. This includes supporting one of the fastest supercomputers in
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Requisition Id 15192 Overview: We are seeking a dynamic and innovative Scientific Lead for developing Quantum-Accelerated High-Performance Computing (QHPC) capabilities. This role includes leading
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Requisition Id 15301 Overview: We are seeking a Group Leader who will focus on leading and performing research in the area of high-performance computing methods and application to challenging
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professionals to accelerate scientific discovery and engineering advances across a broad range of disciplines. As an important part of the broader High-Performance Computing (HPC) infrastructure, the division