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systems. Includes establishing medical reasoning benchmarks and automated / scalable evaluation methods. Developing recommender algorithms to predict specialty care with large-language model based user
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., diffusion transformers, multimodal representation learning) for modeling high-dimensional biological images. Develop computational methods to reconstruct and simulate 3D tissue architecture and dynamics
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radiolabeling of the resulting constructs. The fellow will conduct interdisciplinary research to develop unique translational therapeutics or methods to quantify the imaging data. Our federally-funded team is
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employ advanced analytical methods in large databases, which include claims data and electronic health record data in conventional structures and in common data models. Our research group prioritizes a
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data using econometric techniques; designing and implementing randomized controlled trials. Experience in quantitative methods including prior coding experience (e.g., in STATA or R) and/or in
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experience in aging, geriatrics, palliative care, or serious illness Experience with quantitative research methods (biostatistics, epidemiology, health services research) Familiarity with large datasets
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manuscripts. Findings will be presented within lab meetings and at scientific conferences. The postdoc will also have the opportunity to contribute to biotype methods development, particularly in refining