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mathematically rigorous approaches to optimize the trade-off between privacy and utility especially in the context of large models. Advance knowledge of key AI methods such as deep learning, algorithm design
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storage and analysis solutions (e.g., key-value stores, object or document storage, graph analytics systems) deployed on HPC computational and storage systems. Co-authorship of peer-reviewed publications
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Oak Ridge National Laboratory, Mathematics in Computation Section Position ID: ORNL-POSTDOCTORALRESEARCHASSOCIATE1 [#27205] Position Title: Position Type: Postdoctoral Position Location: Oak Ridge
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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physics, materials science, applied mathematics, computer science, or a related field, and no more than five years of experience beyond PhD. Preferred Qualifications: Background in quantum magnetism
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Oak Ridge National Laboratory, Mathematics in Computation Section Position ID: ORNL-POSTDOCTORALRESEARCHASSOCIATE [#27204] Position Title: Position Type: Postdoctoral Position Location: Oak Ridge
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Requisition Id 15537 Overview: We are seeking a Postdoctoral Research associate in computational nuclear physics. This position focuses on nuclear theory with an emphasis on nuclear structure and
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Oak Ridge National Laboratory, Mathematics in Computation Section Position ID: ORNL-POSTDOCTORALRESEARCHASSOCIATE2 [#27206] Position Title: Position Location: Oak Ridge, Tennessee 37831
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to numerical methods for kinetic equations. Mathematical topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and
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complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section of the Computer Science and Mathematics (CSM) Division. CSM delivers fundamental and applied research