Full-Time Postdoctoral Scholar @ San Francisco, U.S.
A post-doctoral NIH-funded position is available to perform statistical modeling and analysis of genome-wide SNP data and next-generation sequence data in the Longevity Genomics Research Group (www.longevitygenomics.org) (PIs: Steve Cummings, Greg Tranah, and Dan Evans) at the San Francisco Coordinating Center, a joint program at the Department of Epidemiology and Biostatistics at the University of California, San Francisco (UCSF) and the California Pacific Medical Center Research Institute. We are located in the recently constructed Mission Hall building at the UCSF Mission Bay campus. Our group integrates expression data with genome-wide genetic variation in 8 human cohorts totaling 50,000 participants to identify causal genetic relationships with healthy human aging and cancer.
This position provides the opportunity to lead analysis projects to identify longevity-associated genes in large collections of human cohorts. Tasks will involve management of next-generation sequencing data and SNP genotypes imputed to large reference panels (1000 Genomes and HRC). Statistical modeling will include linear and logistic regression, survival analysis, and longitudinal analysis using mixed effects models.
- PhD in statistics, genetics, mathematics, biology, computer science, bioinformatics, or a related field. Experience in human genetics and/or genetic epidemiology is a plus.
- Experience in statistical analysis, including regression modeling, meta-analysis, and cluster analysis.
- Expertise in the R statistical programming language. Should be able to write functions and should be familiar with the data.table package and Bioconductor.
- Experience with Bash and shell scripting. Experience using high performance compute clusters is a plus.
- Knowledgeable of reproducible research practices, such as markdown, github, and R package development.
- Knowledge of Python is a plus.
- Knowledge of Web frameworks, such as Django, is a plus.