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reproducible methods to complex population, clinical, and molecular data using R, Python, SAS, or related tools, with well-documented code and analytic workflows. Collaborate and communicate effectively with
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instrumentation. Experience with Python, model/API integration, retrieval-augmented generation, tool-using agents, scientific databases, and automated experimental platforms is highly desirable. The candidate is
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and Python Solid background in genomics Prior experience in DNA sequencing and cancer genetics is strongly preferred but not exclusively required as training will be available. Qualifications Education
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preferred, Python OK) and demonstrated ability to communicate research findings evidenced through peer-reviewed manuscripts and conference presentations. Highly desirable additional areas of expertise include
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experience in: Mammalian cell culture. High-performance computing environments. UNIX and Python and/or R. Reverse genetics systems or viral culture. Advanced statistical or computational data analysis
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other multi-omics datasets to identify biomarkers and mechanisms of therapeutic response. Develop computational workflows for spatial biology and imaging data analysis using R, Python, or related tools
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), NGS library preparation and Illumina sequencing Experience with the analysis of large-scale NGS data (bioinformatics) Demonstrated proficiency in bioinformatic analyses in R, Python or similar
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analysis of multi-omics datasets. Prior experience with microbiology techniques. Familiarity with mouse models and proper mouse handling. Skills in at least one programming language (R or Python
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management. Proficiency in R, python, C++, Java or bash as demonstrated through a record of open-source software distribution. Desired qualifications: For applicants to the Statistical Methodology track
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) studies is expected. Solid skills in at least one programming language (R, Python or Perl) and experience working in Linux and/or high-performance cluster environments. A strong ability to perform