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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 5 hours ago
modeling, or machine learning - Experience with large-scale genomic data analysis (e.g., GWAS, QTL, PRS, or multi-omics integration) Strong programming skills in R or Python; familiarity with Bayesian
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expertise in collecting and analyzing high-quality nutrition data from children and families, leveraging large datasets, and applying cutting-edge technologies, including artificial intelligence (AI) and
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and Stata. Working with large datasets, including merging files into the data archive. Creating clear data visualizations to communicate results (including GIS maps). Assisting with the preparation
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to support large-scale studies Lead or assist with project coordination, data analysis, manuscript preparation, and grant development Engage in mentoring and training activities Qualifications Ph.D. in
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Position Details Position Information Recruitment/Posting Title Post Doc Associate Department Engn - Biomedical Engineering Salary Details The minimum of $65,000 Offer Information The final salary
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uses observational field data, experimental data, and field experiments. Salary is $68,000 annually, plus benefits. Expected start date is mid-June 2026. Visa sponsorship is available. For examples
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on projects involving large-scale, longitudinal data. Strong qualitative skills, data management and maintenance of databases, and experience working with community groups are essential. The Researcher will
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information at BNL | Benefits Program Position Description The AI Department within Brookhaven National Laboratory's Computing and Data Sciences Directorate invites exceptional candidates to apply
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inflammatory diseases including diabetes, cardiovascular, and Alzheimer’s disease. Successful candidates will lead projects using multi-omics datasets from large sample sizes of disease relevant tissues/cells
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analysis, power analysis, mixture models, causal inference, psychometrics, sequential and time series analysis, and/or analyzing large datasets are plusses. Strong data management skills are required