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with IMPACT-Y leadership, Drs. Sarah Yip, Chris Pittenger and Godfrey Pearlson. This work will involve: Implementing and validating computational models of cognition and behavior (e.g., reinforcement
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AI can accelerate provenance research processes, including especially the use of Large Language Model based transcription of printed and handwritten documents, and subsequent extraction of knowledge
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, single-cell mRNA transcriptomics, and quantitative/functional antibody assays in human and animal models. Responsibilities The postdoctoral associate will – based on their research interest: Design and
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, pharmacoepidemiology, biostatistics, or a closely related quantitative discipline. Working knowledge of core pharmacoepidemiological concepts, in particular confounding by indication, propensity score approaches, and
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future. This post-doctoral position will investigate the use of knowledge graphs on automatically extracted metadata at a cross-disciplinary global scale. Using LLMs and traditional data engineering
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associative learning. Using mouse models, fiber photometry, circuit-specific viral approaches, in vivo recordings, and a variety of behavioral assays, we investigate how infant brains encode maternal and social
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be hired and paid by Yale, but will be expected to relocate to Columbia, SC for the duration of the position. The key aim of the project is to rethink and expand the range of institutional models we
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are interested in linking selectional and mutational landscapes to patterns of genetic variation associated with human traits and diseases. We do this by integrating evolutionary models with GWAS, biobank, and