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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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quantitative social science field with an environmental/global health lens Experience designing and analyzing survey data Strong quantitative analysis skills, with a minimum of 3 years of statistical programming
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community that spans discovery to clinical implementation. Specific Responsibilities include: experimental design, data acquisition, data processing, statistical computation, methods development, data
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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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, requiring preliminary judgments after the supervisor outlines conceptual approach. Build and organize data as requested by principal investigator or supervisor; use common statistical programs to generate and
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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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meetings Key Responsibilities: Development and implementation of study protocols Participant recruitment and collection of participant and laboratory data Statistical analysis of data Authorship
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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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discipline with strong programming and statistics skills, experience analyzing large datasets (cloud computing/big data workflows preferred), and a track record of completed research projects. Prior experience
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model APIs, cloud computing environments, and R for additional statistical analysis. For decision support prototype development and evaluation, web-based user interface design, human-computer interaction