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collection challenges (e.g., technology, logistics, respondent recruitment). Data Management & Analysis Clean and manage large-scale quantitative survey datasets using R (preferred) and Stata or other packages
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, with guidance from supervisor. May orient and train new staff or students. * - Other duties may also be assigned. DESIRED QUALIFICATIONS: Experience with MATLAB, Python, R, or similar. Experience
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in human cellular immunology, T cell and Treg biology, genomics, functional genomics, fluorescence-activated cell sorting, and spatial imaging. Bioinformatics: develop or increase proficiency in R
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programming, probability theory, and statistical analysis of large datasets using R or Python. A successful candidate should have a Ph.D. in Operations Research, Electrical Engineering, or Industrial
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working with large healthcare datasets (EHRs, claims, registries). Proficiency in R or Python. Strong quantitative skills and familiarity with advanced modeling techniques. Excellent written and verbal
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therapeutics targeting GPCRs with higher specificity and efficacy. Relevant publications: Zhong X, Li Q, Polacco BJ, Patil T, Marley A, Foussard H, Khare P, Vartak R, Xu J, DiBerto JF, Roth BL, Eckhardt M, von
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, particularly in data analysis Experience with statistical analysis (e.g., SPSS, MATLAB) and programming (e.g., R, MATLAB, Python) Experience with fMRI data collection and analysis (e.g., FSL, SPM) Required
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skills in statistical software (e.g. R, Stata, Python) and working knowledge in SQL Excellent written and oral communication skills Strong record of distinguished scholarly achievement, including written
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. Required Qualifications: A doctoral degree (PhD, MD, or equivalent) conferred by the start date. Proficiency in R/Python Experience with scRNAseq, and/or spatial proteomic/transcriptomic data analysis Growth
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or gene editing by CRISPR-Cas9 is required. Experience with flow cytometry and/or mass cytometry analysis is desirable. Interest in learning new technologies is mandatory. Basic R programming skills