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given to candidates studying early China using analytical methods such as zooarchaeology, paleobotany, ceramic analysis, and lithic analysis. The successful candidate will be expected to: Teach one course
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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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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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an interest in applying health services research and policy methods to real-world questions in acute and population health. Key Responsibilities Conduct and manage research projects focused
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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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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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opportunity to contribute to methods development, particularly in refining circuit quantification and biotype stratification approaches to increase the clinical relevance and translatability of the research