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primarily through the compilation, evaluation, dissemination, and archiving extensive nuclear datasets. USNDP also addresses gaps in the data, through targeted experimental studies and the use of theoretical
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reconstruction and tracking performance evaluation Knowledge and programming experience in scientific Machine Learning Working knowledge of large-scale data processing Programming experience in C++, ROOT, and
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of scientific data generation and processing and methods evaluation. Formulate high-quality research ideas and directions in collaboration with mentors in the department. Communicate research progress, challenges
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, or SyCL/OpenCL. Hands-on experience with machine learning, including end-to-end training, tuning, and evaluation of at least one class of models. Working understanding of common machine learning model