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molecular profiling platforms. Experience with data analysis software such as GraphPad Prism, R, Python, or similar platforms. Other Requirements: This position is onsite. The work is performed on-site
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-seq Hi-C Micro-C RCMC Organoid culture systems Mouse models Flow cytometry DNA damage and repair assays Computational genomics and bioinformatics Programming and analytical tools such as: R Python
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or physics Generative AI/transformers, agentic AI, deep learning Computational genomics, network modeling, spatiotemporal/functional data analysis, time-series Strong programming in R and Python; best
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or Python Experience working in high-performance computing environments Familiarity with version control systems such as Git or GitHub Demonstrated scientific writing and publication experience Interest in
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and analytical skills with the ability to interpret complex experimental data (R, Python, genomics data experience) Excellent written and verbal communication skills and a collaborative, team-oriented
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simulations and data analysis. This includes data analysis using Python-based algorithms. Experience with EELS is preferred. Skills This See Experience
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, deep learning Computational genomics, network modeling, spatiotemporal/functional data analysis, time-series Strong programming in R and/or Python; best practices in reproducible research Excellent
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proficiency in statistical programming (e.g., R, SAS, STATA, or Python) Have interest or experience in cancer epidemiology, genomics, and/or social determinants of health Exhibit strong critical thinking
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learning models, and willingness to learn about new methods, is a plus. · Strong programming skills in Python, and Linux Shell; experience in developing methods as open source repositories at e.g. GitHub is