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team integrates innovative high-throughput sequencing technologies, bioinformatics approaches, and multi-scale models to elucidate RNA-mediated endothelial biology in the context of diabetes. In parallel
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, including genomic, transcriptomic, proteomic, and circulating biomarker data. The lab provides access to state-of-the-art computational infrastructure, including high-performance computing (HPC
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transcriptomics. Familiarity with next-generation sequencing data analysis tools. Experience working in Linux environments, including batch job management on shared computing resources. Familiarity with a variety
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related field. Strong experience in bioinformatics and analysis of high-dimensional genomic datasets. Strong programming skills in Python and/or R, and experience with Linux/HPC computing
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transcriptomics. Familiarity with next-generation sequencing data analysis tools. Experience working in Linux environments, including batch job management on shared computing resources. Familiarity with a variety
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biology, biomedical data science, or related analytical methodologies is highly desirable. Experience with software development, cloud computing, data engineering, algorithm design, or scalable