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detailed and accurate records. Ensure compliance with environmental, safety, health and quality program requirements. Maintain strong dedication to the implementation and perpetuation of values and ethics
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engineering or equivalent field and 0-2 years of research experience. Background in quantitative analysis, mathematical modeling, data science and simulation techniques with expertise in optimization techniques
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management machine learning, distributed computing, and resource optimization leveraging the unique computational resources available at ORNL, including the Frontier supercomputer—the world's first exascale
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journals and conferences. This role provides a unique opportunity to work with the world’s first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric
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, industrial energy systems, energy efficiency of manufacturing industry, or other related fields. You will play a crucial role in the planning, execution, and optimization of our technical assistance program
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seeking a Postdoctoral Research Associate to assist in the development, qualification, and deployment of Computational Fluid Dynamics (CFD) simulation codes, methods, and standard processes for thermal
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learning based manufacturing process development and optimization. This position resides in the Materials Joining Group in the Materials Structures and Processing Section, Materials Science and Technology
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the Environmental Risk and Energy Analysis Group. The candidate will work with a multi-disciplinary group of experts in economics, engineering, computer sciences, and physical sciences on the economics and policy
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response Demonstrated expertise in process development/optimization for macro-scale deformation in AM Experience with multi-physics simulations on high performance computing (HPC) and maching learning (ML
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industry. You will have the opportunity to interface directly with program sponsors and lead proposal development teams. Major Duties/Responsibilities: Developing advanced modeling and optimization methods