The Ashley group (Departments of Medicine and Genetics) is looking for a talented and energetic statistical geneticist / computational biologist to join our highly collaborative team working on the application of large scale genomic data to clinical medicine. Comprising graduate students, post docs, genetic counselors and physician scientists, we a re particularly interested in the genetic architecture of inherited cardiovascular disease. We were among the first to apply clinical analysis to human genome sequence data. We actively collaborate with groups at Stanford in Bioinformatics (Altman, Butte), Genetics (Bustamante, Snyder), Bioengineering (Quake), Statistics (Tibshirani) and Computer Science (Koller). Data sets include genotype array and exomes in the thousands, whole genomes in the 100s and, upcoming, transcriptomes in the thousands. We are mildly obsessed with network analysis and have an emerging interest in high performance computing as well as creative solutions to the I/O problem.
A computer science, bioinformatics or similar PhD and a background in statistical analysis of genotype array and sequence (gDNA, RNA) data in individuals, families and/or cohorts are minimum requirements. The strongest candidates will have working knowledge of a variety of tools for genetic association inference, including linkage, genome wide association, and set based association tests (e.g. collapsing, burden, and kernel association tests). Fluency in R, python, perl and familiarity with BWA, GATK and supporting tools are essential, as is an ability to evaluate and deploy newly developed open source tools. A track record in the development of new tools and Java/C skills would be ideal. Experience in management of a local cluster is required (version control, basic admin tasks). Opportunities for scholarship and mentorship will be readily available. Excellent verbal and written communication skills are required, as is a willingness to work with colleagues with a broad array of computational literacy and expertise. Competitive salary and benefits will be provided commensurate with experience.
For the right candidate, this is a spectacular opportunity to join a vibrant group at the very heart of Stanford’s research and clinical genomics/bioinformatics community.
Please email your CV to Terra Coakley at tcoakley@stanford.edu to be considered.
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