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Qualifications: Ph.D. or equivalent in Medical Physics, Biomedical Engineering, Electrical Engineering, Material Science, Chemical Engineering, or Chemistry/Biology or an MD or equivalent with experience in
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on topics including mathematical foundations of data science and statistical/machine learning, with an emphasis on inverse problems and in-context learning for PDEs and interacting particle systems
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motivated with a passion for investigating policy impacts and have strong analytic and writing skills. The Fellow may have a PhD in health policy, biostatistics, economics, or a related field, or an MD with
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