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.) ● Strong computational background, including: o 2 years of experience in programming (e.g., Python, R, Julia, or similar); o Evidence of working with large-scale datasets (e.g., genomics, transcriptomics
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research, or a related discipline, or an MD degree with demonstrated research experience in computational or quantitative methods. Strong programming skills in languages such as Python, R, or SQL would be
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, Python, Mplus, or similar) - Familiarity with big data, Linux systems, and remote computing clusters - Experience with genome-wide statistical genetics approaches (e.g., GWAS, genetic correlations, PGS
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. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
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processes contributing to sea level change; b) experience with ocean and/or earth system modeling; c) experience with Python and scientific data analysis. Candidates must have a Ph.D. or expect to complete a
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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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deep learning including data collection, architecture development, model training, and validation Interest in software development, with particular emphasis on the Python programming language and
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Geosciences, Environmental sciences, Civil or Environmental Engineering, Physics or Mathematics or a related discipline Experience in programming (e.g., Python, MATLAB, or similar), interest in machine learning
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human subject research in clinical populations with impaired neuromuscular control, especially those with acute or chronic concussion Programming experience (MATLAB, Python, R) Experience using
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human subject research in clinical populations with impaired neuromuscular control, especially those with acute or chronic concussion Programming experience (MATLAB, Python, R) Experience using