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the position description. Preferences The ideal candidate will have experience with wearable sensors and/or remote monitoring approaches and strong programming (e.g., R, Python, or similar) and writing skills
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 1 month 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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, Medicine, Global Health, Respiratory Medicine). Strong background in epidemiology, clinical research, or biomedical sciences. Proficiency with data analysis and statistical software (e.g., R, SPSS, Stata
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in Python and R for data analysis, modeling, and visualization. Proficiency in building efficient pipelines that use optimized software to process large datasets. Proficiency in supervised
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., SPSS, R, Mplus) and data management systems (e.g., REDCap, Qualtrics). Experience contributing to or managing federally funded research projects. Additional Candidate Instruction Applicants should submit
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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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, such as R, SPSS, Stata, MAXQDA, and Nvivo. Aid in the analysis of data to derive insights into best practices for practitioners and recommendations for policy makers. Ability to present research findings
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software to create maps. Experience with data entry and data QA/QC protocols to support ecological and forestry research. Knowledge of Microsoft Excel highly preferred, familiarity with ArcPro and R also
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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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in genome and exome sequencing analysis. Expertise in bulk and single-cell RNA sequencing analysis. Proficiency in programming languages such as Python and R for data analysis, modeling, and