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Qualifications: PhD (or equivalent) in Biostatistics, Epidemiology, or a closely-related quantitative field (by start date) Strong training in causal inference methods Experience working with large-scale
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the resulting data from the experiments. Required Qualifications: Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including
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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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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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: 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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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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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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a licensed clinical psychologist Supervise undergraduate and graduate research assistants Required Qualifications: Doctoral degree (PhD or PsyD) in Clinical Psychology, Developmental Psychology
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translational oncology, and a vibrant research community that spans discovery to clinical implementation. Specific Responsibilities include: experimental design, data acquisition, data processing, statistical