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Qualifications Completion of a certified machinist apprenticeship program. Knowledge of machine shop theory and procedures, shop mathematics, machinability of materials, layout techniques and shop safety. General
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interpret quantum computational results with respect to experimental data and/or classical theory/simulation. Collaborate with ORNL staff scientists and external collaborators. Write peer-reviewed scientific
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hardware. As part of our team, you will perform research to develop new scalable quantum simulation algorithms, based on multi-linear representation theory, and apply them to real world applications spanning
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broad understanding and wide application of engineering principles, theories, and concepts as well as general knowledge of power systems-related disciplines, applications and challenges. Specifically
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approaches to optimize the trade-off between privacy and utility especially in the context of large models. Advance knowledge of key AI methods such as deep learning, algorithm design, probability theory
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with one or more prominent computational science software packages in the area of Lattice Gauge Theories (Chroma, CPS, MILC, QUDA, Grid, etc.) is highly desirable. Familiarity with C/C++ and accelerator
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temperatures based on these predictions. The position resides in the Nanomaterials Theory Institute (NTI) within the Theory and Computation Section (TACS) at the Center for Nanophase Materials Sciences (CNMS
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scientific community. Major Duties/Responsibilities: Develop, improve, and implement novel energy-water theories, techniques, and models to promote the growth and resilience of domestic power generation. Lead
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, including BLDC, PMSM, AC, DC, and induction motors. Strong understanding of electromagnetic theory, motor operating principles, and electrical motor design. Experience with optimization techniques