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radiative transfer, and/or precise calibration of astrophysical data. Relevant references: - JWST data: https://ui.adsabs.harvard.edu/abs/2024ApJ...963..158P/abstract - JDISCS: https://ui.adsabs.harvard.edu
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Disease Prevention and Health Promotion in the Division of Nutrition, Physical Activity, and Obesity (DNPAO), you will engage in a training experience involving Active People, Healthy Nation (https
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, such as R, Python, and statistics, and to learn collaboration and leadership skills through workshop and group experience. USDA-ARS Mentor: If you have questions about the nature of the research, please
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, such as R, Python, and statistics, and to learn collaboration and leadership skills through workshop and group experience. USDA-ARS Mentor: If you have questions about the nature of the research, please
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include some combination of R and/or Python, competency with reproducible documents (e.g., quarto), experience working with collaborative coding platforms (e.g., git), probabilistic programming languages
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for CLIA laboratory, including SOP use, assay controls, stability assessment, and discrepancy review. Gain experience analyzing assay performance metrics using tools such as R, Python, or laboratory data
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, or doctoral degree in the one of the relevant fields. Preferred skills: Fluent R and high-proficiency Python programming for data analysis, modeling, and scripting Courses or training that includes
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written, verbal, and interpersonal skills; Background in epidemiology and/or maternal and child health; Education or experience analyzing data using SAS, R, Python and/or other statistical software
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, game-theoretic analysis, network problems, decision analysis, or behavioral economics Proficiency in a scientific computing or statistical programming languages (e.g., Python, R, Julia, C++, or MATLAB
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Proficiency in Python for geospatial data handling, model workflows, and scientific computing Strong communication skills and enthusiasm for interagency scientific research Application Requirements A complete