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demonstrated through peer reviewed publications and presentations at national/international conferences. Coursework in advanced epidemiologic methods (causal inference models), environmental mixtures, and
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include computational biology and/or biomedicine, multi-modality fusion and inference (visual and NLP data), computationally efficient ML, environmental sciences, business applications, chemistry, and
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well-being while reducing inequities. Experience with place-based research, causal inference, and program evaluation involving community-based organizations, law enforcement, government agencies, and
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Center for Computational Cognitive Neuro-Psychiatry (CCNP; https://ccnp.princeton.edu/about-ccnp/ ), including through an NIH-funded center on Latent Cause Inference (https://lci-conte.pni.princeton.edu
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well-being while reducing inequities. Experience with place-based research, causal inference, and program evaluation involving community-based organizations, law enforcement, government agencies, and
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Center for Computational Cognitive Neuro-Psychiatry (CCNP; https://ccnp.princeton.edu/about-ccnp/ ), including through an NIH-funded center on Latent Cause Inference (https://lci-conte.pni.princeton.edu
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Required Knowledge, Skills, and Abilities Excellent quantitative analytical skills, particularly in longitudinal modeling, administrative data analyses, and causal inference methods. Understanding of HIPAA