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of dissertation topics: Development of Machine Learning Frameworks for Reactive Atomistic Materials Modeling (DSP II) Profile of the graduate This Ph.D. program is an interdisciplinary study combining physical
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qualitative (elite interviews, focus groups, comparative case studies, archival work…) and quantitative (surveys and survey experiments, statistical analyses of time series/cross-sectional data, NLP/machine
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