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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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unravel the complex relationships between land use changes and fire regimes over the past 60 years. The successful candidate will lead efforts to: Develop advanced deep learning algorithms for classifying
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imbalanced cross-sectional imaging data are especially well-suited for the position . The postdoctoral researchers will develop algorithms for deployment at our prestigious R Adams Cowley Shock Trauma Center
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. This includes integrating LLMs with structured data sources to develop robust computational phenotyping algorithms and scalable models for real-world evidence generation. The role will involve both method
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@stanford.edu (link sends e-mail) Does this position pay above the required minimum?: Yes. The expected base pay range for this position is listed in Pay Range field. The pay offered to the selected candidate