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and scholarship into practical contributions for academia and public life. The Research & Design Studio: The Research & Design Studio (R&DS) is an interdisciplinary network that bridges scholarship and
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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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surveys; Programming/scripting knowledge suitable for processing raw data for analysis (e.g., text manipulation); One or more computational environments for statistical analysis (e.g., MATLAB, Stata, R
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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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surveys; · Programming/scripting knowledge suitable for processing raw data for analysis (e.g., text manipulation); · One or more computational environments for statistical analysis (e.g., MATLAB, R
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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
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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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Bioinformatics, Computational Biology, or related areas; Hands-on experience with, or a strong interest in, bioinformatics programming, including Linux, scripting, and R; Expertise in data mining and cleaning