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at Stanford, this position offers the opportunity to work with some of the most detailed data in clinical medicine — including second-by-second EHR metadata and continuous physiologic monitoring — to study how
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from real world longitudinal data on management and health outcomes for children with mental health conditions. Methods have included deep learning, large language models (LLM), generative AI models (Gen
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of prevention (cardiovascular and cancer genetic epidemiology, genetic risk scores, and gene-environment interactions) Technologies for intervention and assessment of health behaviors and conditions (ambulatory
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-shot learning approaches for diagnosing and treating patients with rare diseases? Can we design clinically-useful metrics for evaluation and continuous monitoring after deployment? This position is
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developing novel techniques for diagnosing, monitoring, and treating oculoplastic and orbital disease. A post-doc in the oculoplastics lab will work on translational studies such as cell culture projects