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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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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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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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: 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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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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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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translational oncology, and a vibrant research community that spans discovery to clinical implementation. Specific Responsibilities include: experimental design, data acquisition, data processing, statistical
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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