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latent variable models (especially factor analysis, item response theory, and growth modeling) and coding in R. Strong collaborative skills and ability to work well in a complex, multidisciplinary
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Expertise and hands-on experience using LLMs, Machine Learning, Deep Learning frameworks, Natural Language Processing, etc. Proficient programming skills in Python and R and working knowledge in SQL Strong
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.) and proficiency in data analysis software (such as R, Mplus, SPSS). Extensive experience interpreting research data and summarizing findings via written reports and oral presentations. Strong record
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to the microbiome/metabolome. Superb quantitative background, strong coding skills (e.g., Python, R, MATLAB). Strong computer skills, experience with databases and scientific applications, and ability to quickly
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the use of R and/or Python Basic understanding of statistical modeling, and machine learning Understanding of high-throughput sequencing techniques including whole genome, whole exome, targeted capture, RNA
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knowledge in bioinformatics, machine learning, statistics and programming skills (R, Python, or MATLAB) are required. The ideal candidate should demonstrate a record of publications in the area. Knowledge in
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, mathematics, physics, or a related field. The ideal candidate should demonstrate a record of publications in the area. Strong knowledge in machine learning, statistics and programming skills (R, Python
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expertise in molecular and cell biology are encouraged to apply. Basic to advanced experience with computational analysis and R/Python. Excellent oral and written communication skills and be able to work
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and prior DNA repair experience will be prioritized. Basic to advanced experience with R and/or Python. Excellent oral and written communication skills and be able to work effectively with collaborating
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(e.g., R, Stata, Python). • Excellent written and verbal communication skills. • Demonstrated ability to work independently and as part of a team. Preferred (but not Required): Experience conducting