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collaborating on dissemination through open-source R packages and associated tutorials. This position provides an opportunity to produce high-impact methodological research while engaging in applied health policy
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collaborating on dissemination through open-source R packages and associated tutorials. This position provides an opportunity to produce high-impact methodological research while engaging in applied health policy
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simulation studies, applying the methods to electronic health records (EHR) and clinical trial datasets, and collaborating on dissemination through open-source R packages and associated tutorials
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appointment). Strong background in statistical or machine learning methodology, optimization, or high-dimensional data analysis. Proficiency in R or Python; experience with deep learning, causal inference
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-dimensional data analysis. Proficiency in R or Python; experience with deep learning, causal inference, or genetic data analysis is not required but encouraged. Excellent written and verbal communication skills
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, math, statistics, and/or computer science Experience with programming, data science, and geospatial analysis (especially R, Stata, Julia, MATLAB, or Python) An enthusiasm for empirical research and an
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for analysis (e.g., text manipulation); · One or more computational environments for statistical analysis (e.g., MATLAB, R, or Stata); · Creating and managing very large datasets; · Machine
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environments for statistical analysis (e.g., MATLAB, R, or Stata); · Creating and managing very large datasets; · Machine learning skills. Basic Qualifications A Ph.D. in any business discipline
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analysis (especially R, Stata, Julia, MATLAB, or Python) An enthusiasm for empirical research and an interest in pursuing a PhD in economics or related fields (e.g., public policy) An ability to work
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required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Additional Qualifications