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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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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 4 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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, accessibility, or universal design. Experience with AR/VR tools, programming/coding (Python, R, Unity, or JavaScript), or community-engaged research. Experience working in interdisciplinary teams and multi-site
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. Preferred Qualifications Knowledge of aging-in-place, accessibility, or universal design. Experience with AR/VR tools, programming/coding (Python, R, Unity, or JavaScript), or community-engaged research
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Qualifications Education: ABD status by start date. PhD by start date in a field relevant to the research being conducted. PhD after one year of employment. Technical Skills or Knowledge: Proficiency in Python
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. Knowledge, Skills & Abilities : Strong programming skills (Python required; Java/Android or App Inventor experience desirable). Familiarity with statistics and machine learning methods. Interest in
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simulations and perform computational experiments using high-level programming languages (e.g., Python, MATLAB, R, or Julia). Curate and integrate experimental data to calibrate and validate models, including
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the U.S Experience working with spatial data and machine learning models. Strong knowledge of programming languages, such as Python, R . Demonstrated skills in scientific writing, publications, and
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measure leg-generated forces. Investigate relationships between neural activity, muscle properties, and joint movement. Code in MATLAB or Python for data analysis, modeling, and tracking tasks. Assist with
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• Understanding of agricultural production systems in the U.S • Experience working with spatial data and machine learning models. • Strong knowledge of programming languages, such as Python, R . • Demonstrated