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22.C51 Modeling with Machine Learning: Nuclear Science and Engineering Applications

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(Subject meets with 22.C01)
Prereq: Calculus II (GIR), 6.100A, and 6.C51
Units: 2-0-4

Building on core material in 6.C51, focuses on applying various machine learning techniques to a broad range of topics which are of core value in modern nuclear science and engineering. Relevant topics include machine learning on fusion and plasma diagnosis, reactor physics and nuclear fission, nuclear materials properties, quantum engineering and nuclear materials, and nuclear security. Special components center on the additional machine learning architectures that are most relevant to a certain field, the implementation, and picking up the right problems to solve using a machine learning approach. Final project dedicated to the field-specific applications. Students taking graduate version complete additional assignments. Students cannot receive credit without completion of the core subject 6.C51.
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