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environment spanning the Department of Biostatistics, the Brown Data Science Institute, and interdisciplinary collaborators at Harvard University, Fred Hutch Cancer Center, and across clinical and public health
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, Python, and SAS or Stata) • Demonstrated expertise in causal inference and high-dimensional risk adjustment/predictive modeling, experience with Medicare claims data • Clear scientific writing and
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, representation learning) Spatiotemporal modeling or geospatial/temporal data analysis Medium-to-Large-scale foundation models pretraining/fine-tuning paradigms Strong programming skills in Python and experience
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] that process information in temporal rather than spatial modes to reduce their footprint. The project involves a collaboration between DTU Electro (Senior Researcher Mikkel Heuck) and Harvard University (Dr
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-to-date research topics Opportunities to work with the top peers from Harvard University, NASA JPL, Caltech, UC Berkeley, and other European partners, e.g. LSCE (France), EMPA (Switzerland) INTERESTED? We