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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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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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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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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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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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for individual-, longitudinal-, and group-level inference Applying advanced statistical models for longitudinal data (e.g., mixed-effects models, missing-data handling) Integrating imaging outputs with behavioral
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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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programming, probability theory, and statistical analysis of large datasets using R or Python. A successful candidate should have a Ph.D. in Operations Research, Electrical Engineering, or Industrial
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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