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global supply chain logistics. While ML has the potential to transform both applied large-scale optimization and theoretical combinatorial optimization, algorithmic reasoning remains a significant
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how we decode cancer biology from spatial multi-omics data. This position offers an exceptional opportunity to build next-generation generative models for complex biological systems, working with large
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paradigms in primates or humans – Theoretical neuroscience, machine learning, or AI • Proficiency in Python, MATLAB, or equivalent data‑analysis frameworks. • A passion for big‑picture questions, open science
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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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into tangible products. Critically, this work will generate a large open-source dataset of child-created games that can inform future designs of educational games and AI algorithms. The postdoctoral fellow will
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urgent questions of practical relevance and to design studies to test pragmatic solutions, analyze data, and disseminate findings and implications. The program will also provide fellows with training in
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on emergency medicine health services, care transitions, and population-level outcomes. Utilize advanced quantitative methods to analyze large healthcare datasets, including Medicare and Medicaid claims (MedPAR
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, and to utilize the unique data provided by tutoring to better understand teaching and learning. The postdoctoral fellow will contribute to this work by leading one or more of the following research