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. Preferred: Integration of wet lab findings with computational analysis of multi-omic data (e.g., structural variants, transcriptomics) using R or Python pipelines. Mentoring and Professional Development
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-omic data integration. Computational skills for data analysis (e.g., Python/R, workflow tools, and reproducible research practices). Prior work related to neurodevelopmental disorders, regulatory
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fitting, parameter estimation, and model comparison Proficiency in at least one scientific programming language (e.g., Python, MATLAB, R) Demonstrated ability to work independently while collaborating
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cancer models Experience with single-cell/single-nucleus genomics and spatial transcriptomics Computational analysis skills in R and/or Python A record of first-author publication To apply: Please send a
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journals; (c) experience or interests in programming languages such as R or python; (d) willingness to work with HIV+ samples following BSL2+ procedures; (e) willingness to work with mouse models; (f
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programming skills in Python, R, or similar languages. Experience working with large biological datasets. Familiarity with Linux-based computing environments and high-performance computing. Excellent analytical
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Required: PhD in Bioinformatics, Computational Biology, Computer Science, or equivalent related field Strong programming skills (R and Python required; PyTorch/JAX/TensorFlow preferred) Demonstrated track
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epidemiology. Experience analyzing large cohort, registry, biobank, or omics datasets. Strong programming skills in R, SAS, Stata, or Python. Familiarity with survival analysis, longitudinal data analysis
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, or qualitative research -Prior experience with software such as R/RStudio and Epic electronic health records -Able to lead independent projects but work collaboratively with team Process to Apply: If interested
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interests relevant to perinatal or pharmacoepidemiology, are preferred. The position will require extensive experience with programming languages and statistical software packages, such as R or SAS