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and pursue independent research directions. Required Qualifications: Completed PhD in Statistics, Biostatistics, Computer Science, Bioinformatics, or a closely related area prior to their appointment
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PhD graduates who are passionate about leveraging computational methods to transform trauma and acute care surgery. Fellows will work at the intersection of clinical medicine, data engineering, and
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disease, including AI-powered tools and new statistical techniques that leverage large datasets, heavy computational capabilities, and/or a robust understanding of biological systems to provide unique
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: Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including bioengineering, computer science, statistics, or mathematics. Strong
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with researchers both at Stanford and the U.S. Census Bureau. The position is open to recent graduates of PhD programs in economics, statistics, sociology or related data science fields, preferably with
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Qualifications: PhD with substantial expertise in data science, geospatial techniques, and statistical/causal inference Required Application Materials: CV 1-page cover letter describing research background and
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strong background in applied statistics, but lack experience addressing policy-relevant questions, analyzing large datasets, or working in applied settings. Applicants from non-traditional backgrounds
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graduates of PhD programs in statistics, economics, computer science, operations research, or related data science fields. The position provides opportunities to participate in rigorous, quantitative research
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, biologics, and cannabis. Apply statistical and machine learning approaches (e.g., sequence analysis, latent class analysis, clustering) to examine medication use trajectories and patient subgroups
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Qualifications: PhD or MD/PhD in a field(s) relevant to functional neuroimaging and neuroimaging data analysis. Extensive experience with functional magnetic resonance imaging, including resting fMRI and task fMRI