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of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a
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topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and iterative solvers. Successful applications will work
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states, magnetic phase transitions, and corresponding structural responses at high magnetic fields, using high flux neutron scattering techniques. Additionally, collaborative work will be performed with
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research, each year carrying out more than 1,000 experiments in the physical, chemical, materials, biological and medical sciences. To learn more about Neutron Sciences at ORNL, please go to this link: http