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University is recruiting postdoctoral scholars with prior training in statistics, biostatistics, computer science, bioinformatics or a closely related area. Applications are invited from ambitious, independent
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bioengineering, computer science, statistics, or mathematics OR a strong background in gene engineering and functional interrogation of hematopoietic stem and progenitor cells. Strong knowledge in bioinformatics
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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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analysis skills, with a minimum of 3 years of statistical programming experience with R (possibly also Stata, Python or other statistical software) Excellent oral and written English-language communication
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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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econometrics) or relevant research experience. • Strong coding skills in R, Stata, or other statistical software package. • Good communication skills in English. Required Application Materials: CV (no cover
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is a plus. Candidates should also demonstrate strong skills in Python (for ML/NLP tasks) and R (for statistical modeling or data analysis), as both will be actively used in the research workflow
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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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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