16 structures "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dip" "Dip" "Dip" Postdoctoral research jobs at Oak Ridge National Laboratory in United States
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to ORNL's Research Code of Conduct. Our full code of conduct, and a statement by the Lab Director's office can be found here: https://www.ornl.gov/content/research-integrity Benefits at ORNL: UT Battelle
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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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Requisition Id 15408 Overview: Oak Ridge National Laboratory (ORNL) (https://www.ornl.gov/) is the largest US Department of Energy science and energy laboratory, conducting basic and applied
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to ORNL's Research Code of Conduct. Our full code of conduct and a statement by the Lab Director's office can be found here: https://www.ornl.gov/content/research-integrity . Basic Qualifications: PhD in
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(https://www.olcf.ornl.gov/frontier ) and plant phenotyping (https://www.ornl.gov/appl ). GPTgp is a pilot project initiated in September 2025 with funding from the US Department of Energy and will
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to commit to ORNL’s Research Code of Conduct. Our full code of conduct and a statement by the Lab Director’s office can be found here: https://www.ornl.gov/content/research-integrity Basic Qualifications
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, finite volume, and machine learning to solve challenging real-world problems related to structural materials and advanced manufacturing processes. The successful candidate will have experience with
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Postdoctoral Research Associate - Theory-in-the-loop of Autonomous Experiments for Materials-by-Desi
of NTI and CNMS to develop HPC workflows that can perform multi-fidelity simulations to predict and interpret a wide range of structural and electronic characterization techniques Develop physics-informed
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-based systems Background in topology optimization and structural design Experience in thermomechanical characterization of polymer materials Demonstrated experimental capabilities and a strong