33 estimation-methods Postdoctoral positions at Oak Ridge National Laboratory in United-State
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is to integrate computational modeling with experimental methods and provide innovative solutions for technology growth. We aspire to help generate technical artifacts (patents) as well as scientific
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to accelerate the design and discovery of novel materials. The Materials Theory Group has a background in using first principles methods to examine electronic and thermal transport, magnetic properties
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Requisition Id 15421 Overview: The Multiscale Methods and Dynamics (MMD) Group at Oak Ridge National Laboratory (ORNL) is seeking several qualified applicants for postdoctoral positions related
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materials. In this role, you will develop and apply methods that integrate physics‑guided image correction with intelligent (AI/ML‑enabled) data‑acquisition strategies. Key objectives include (1) implementing
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, Integrity, Teamwork, Safety, and Service Preferred Qualifications: Deep expertise in atomistic and multiscale simulation methods (e.g., MD, enhanced sampling, QM/MM) Experience improving performance and
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experiments. You will play an integral role in electron microscopy and closely collaborate with other scientists for synthesis, theoretical calculations, and other characterization methods across multiple
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techniques; and (3) developing advanced methods for inelastic neutron scattering data analysis and workflow automation. The postdoctoral researcher will work in close collaboration with Dr. Raphaël Hermann and
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seeking postdoctoral candidates to investigate the mechanical and thermophysical behavior of irradiated metals and ceramics using advanced experimental and computational methods. The selected candidates
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Programming experience in scientific computing environments Preferred Qualifications: Experience developing Finite Element Method or CFD models for composite manufacturing applications Knowledge of machine
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research methods on large, domain-specific scientific datasets. Major Duties/Responsibilities: Designing and developing foundational AI-driven techniques for the generation and exploration of complex, large