39 structural-optimization "https:" Postdoctoral positions at Oak Ridge National Laboratory
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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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research analysis on geothermal well development and other advanced energy technologies that could achieve transformative gains in energy efficiency. Ability to develop optimization and life cycle models
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developing the technical basis for the first fusion nuclear facility and the position will involve several disciplines, with an intended focus on design, analysis, and optimization of fluid flows in tritium
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understanding of machine learning methodologies and data science methodologies and techniques, (e.g. supervised and unsupervised learning, feature selection/engineering, hyperparameter optimization
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characterizations. Experience with user facilities. Data analysis of structural, electronic, magnetic, and topological properties. Work with others to maintain a high level of scientific productivity. Publish
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
-state physics, ferroelectrics and/or 2D materials. Strong background in developing and/or applying materials simulation methods, such as atomistic simulations using electronic-structure and/or machine
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Requisition Id 15537 Overview: We are seeking a Postdoctoral Research associate in computational nuclear physics. This position focuses on nuclear theory with an emphasis on nuclear structure and
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including code design, documentation and testing. Familiarity with optimization methods including Machine Learning (ML) techniques. Any experience with computations on GPUs. Working knowledge of Linux command
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, Educational Assistance, Relocation Assistance, and Employee Discounts. We are not accepting applications for this job through MathJobs.Org right now. Please apply at https://jobs.ornl.gov/job/Oak-Ridge
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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