41 structural-engineering-"https:"-"https:"-"https:"-"UCL" Postdoctoral positions at Oak Ridge National Laboratory
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Requisition Id 15794 Overview: The Physics Division at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate to join the Nuclear Structure and Nuclear Astrophysics
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challenges facing the nation. The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral
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. Research will involve growth of single crystals and measurements to understand their structural and physical properties including magnetism and thermal transport, as well as helping to identify new magnetic
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the Quantum Heterostructures Group in the Foundational & Quantum Materials Science Section, Materials Science and Technology Division, Physical Sciences Directorate at Oak Ridge National Laboratory (ORNL). As
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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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management skills are required. This position resides in the Deposition Science and Technology Group at the Manufacturing Demonstration Facility (MDF) in the Manufacturing Sciences Division (MSD), Energy
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scientists, engineers, and facility operators to integrate AI seamlessly into experimental and computational pipelines. Demonstrate the effectiveness of dynamic workflows in representative use cases such as
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Requisition Id 15823 Overview: We are seeking a postdoctoral researcher skilled in biogeochemistry who will contribute to mercury remediation technology development program, specifically focusing
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deformation + irradiation and/or corrosion) that affect the performance of structural materials deployed in extreme operating conditions and develop advanced characterization techniques to achieve these goals
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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