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undergraduate student Excellent research, analytical, and writing skills Experience or Familiarity with Python or R Ability to work independently and as part of a team Preferred Qualifications Strong interest
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judged from published papers or publicly available (e.g., arXived) preprints, will be given priority. Strong programming skills in R/Python/MATLAB with some knowledge of C/C++ will be preferred. Prior
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Pharmacoepidemiology, Health Services Research, Public Health, Biostatistics, or a related discipline Demonstrated commitment to addressing health disparities Strong quantitative skills (e.g., SAS, R, STATA) Excellent
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using R for statistical analysis and in statistical modeling. Sound working knowledge of unix shell, high performance compute clusters and git. Willingness to learn and use a scripting language (e.g
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the following areas: Performing and/or analyzing functional genomics experiments Competence with Unix environment, R, Python, high performing cluster Familiarity with machine learning Have taken coursework in
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interpersonal, communication, organizational, problem-solving, and statistical software skills (e.g., R). Strong background in quantitative data analysis and research methodology is preferred. Ideal candidates
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coding environments (e.g., R, Python). Ability to work collaboratively with a team of diverse backgrounds. Excellent written and verbal communication skills. Experience in processing large data sets
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optimization. • Proficiency in programming (Python, R, Julia, or similar) and experience with frameworks like PyTorch, TensorFlow, or JAX. • Prior research in statistical learning and online optimization
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The successful applicant will hold a Ph.D. in agricultural economics or related fields. The successful applicant should have experience using statistical programming languages, such as R, Python, SAS, etc
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languages such as R or Python is preferred. Candidates should have strong interpersonal skills, work well in research teams, nurture a professional environment, and have a strong commitment to rigorous