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Methods and Dynamics (MMD) Group at Oak Ridge National Laboratory (ORNL) is seeking several qualified applicants for postdoctoral positions related to Computational Fluid Dynamics. Mathematical topics
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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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APPFL and OmniFed. Major Duties and Responsibilities: Conduct and publish original research focused on data readiness methodologies and frameworks for scalable AI applications across fluid dynamics
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) and Computational Fluid Dynamics (CFD), for polymer composite manufacturing processes Perform multi-physics simulations involving coupled thermal, mechanical, and material behavior across multiple
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: Experience in one more of the following areas: Mathematical methods for kinetic and/or fluid equations Multiscale problems and model reduction Modern machine learning software tools and frameworks
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developing the technical basis for the first fusion nuclear facility and the position will involve several disciplines, with an intended focus on design, analysis, and optimization of fluid flows in tritium
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for kinetic and/or fluid equations Multiscale problems and model reduction Modern machine learning software tools and frameworks Implementation of scalable numerical algorithms on HPC architectures Excellent