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at temperatures of 50 mK-350 K and at fields of up to 15 T with emphasis on the development of new sensing protocols optimized for high-field and low temperature environments. In addition, these sensors will be
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workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A Ph.D. in evolutionary biology, ecology, plant biology, genomics, bioinformatics, computer science, plant
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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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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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emerging at the grid edge, providing essential services crucial to its reliable operation. Employing a diverse range of disciplines such as control theory, optimization, economics, game theory, data
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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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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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. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in mechanical engineering, industrial engineering
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-making processes. Build strong collaborations within ORNL and across the global research community. Publish groundbreaking research in top-tier machine learning conferences and journals. Be a part of a