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skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and
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, design and analysis of virus-derived RNA libraries, and development of machine learning models for detecting functional elements in viral metagenomic datasets. This project is a collaboration with the
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, the Peabody Museum, or more technical parts of the University for periods of time to learn about both research and operational workflows. Connections with the Wu Tsai Institute, the AI at Yale program, the Data
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platforms a plus Experience applying machine learning, artificial intelligence, and large language models to research a plus The anticipated start date is September 1, 2026. The postdoctoral position incoming
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. Education and scholarly development The postdoctoral associate will receive structured education in computer vision applications in medical imaging, machine learning, research methodology, responsible conduct
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causal inference, machine learning, and artificial intelligence is desirable ● Experience with clinical, EHR, or biobank data analyses is desirable Application Instructions To apply: Interested