11 phd-mathematical-modelling Postdoctoral positions at Oak Ridge National Laboratory
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respectful workplace – in how we treat one another, work together, and measure success. Required Qualifications: PhD in Nuclear engineering, computer science, applied mathematics, or a related field completed
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-flows. Basic Qualifications: PhD in mathematics, computer science, engineering, or related field earned within the last 5 years. Preferred Qualifications: Experience with mesh generation/CFD applications
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in professional organizations Basic Qualifications: A PhD in Mathematics, Applied Mathematics, Computational Science, or a related field completed within the last 5 years Preferred Qualifications
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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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collaboration. Present and report research results and publish scientific results in peer-reviewed journals or conferences. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational
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and conference presentations Active participation in professional organizations Basic Qualifications: A PhD in Mathematics, Applied Mathematics, Computational Science, or a related field completed
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thermomechanics. Major Duties/Responsibilities: Help to develop and apply physics-based and/or machine learning models for advanced manufacturing processes. Author peer reviewed papers for journals and conference
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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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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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workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in evolutionary biology, plant biology, genomics, bioinformatics, mathematics, statistics, computer