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data, weather records, and high-resolution air pollution and related environmental exposures data. Motivated by relevant public health and policy questions, the goal is to develop methodologies
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(https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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leverages nationwide Medicare claims data for older adults in the United States, linked with rich contextual information, including census, weather, and air pollution data. The overarching goal is to develop
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impact. Our team leverages data pipelines to quantify data centers’ electricity and water use, emissions, and air pollution exposure and health impacts. The overarching goal is to develop an interactive
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and neural activity. In particular, Postdoctoral AI Researchers may help develop brain foundation models that predict patterns of neural activity from large-scale, multi-regional recordings. Areas
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AI/ML and a strong record of research accomplishment who are excited to develop new AI approaches for high-impact problems in cellular and protein computational biology. This role focuses on applying