Please forward application materials to Dr. Assimes firstname.lastname@example.org and cc: Phil Tsao email@example.com and our administrative assistant, Dalia Cristina Gonzalez firstname.lastname@example.org.
We receive many applications and inquiries about post-doctoral positions making it challenging to respond to every email . We will generally only respond to those who are clearly a good match for our lab and research missions in terms of their education, experience, and experience to date.
Successful applicants will be immersed in cutting-edge molecular epidemiology studies of traits related to cardiovascular disease using large scale population biobanks including the Million Veteran Program (>825k including ~19% African American and 7% Hispanic participants), the Women’s Health Initiative (>140k), and the UK Biobank (500k), with the goal of improving biological understanding, refining risk prediction, and discovering new therapeutic targets. A major emphasis of ongoing work is robustly extending genomic discoveries into under-represented populations including African American and Hispanic populations, as well improving portability of genetic risk prediction algorithms into the same populations in anticipation of testing the clinical utility of these algorithms within integrated health care systems serving diverse populations including the Veterans Health Administration.
Potential areas of research include the following funded projects:
• Genetics of Cardiometabolic Diseases in the Veteran Affairs Population (I01 BX003362)
• Proteomic Determinants of direct measures of insulin sensitivity (1R01DK114183)
• Whole-genome sequencing analysis of coronary atherosclerosis and related traits (1R01HL146860)
• New methods for constructing and evaluating polygenic scores (1R01HG011432)
• Genome-wide association study of coronary artery disease in individuals of African ancestry (1R56HL150186)
• Polygenic Risk Scores (PRS) for Diverse Populations - Bridging Research and Clinical Care (1R01HL151152)
Stanford University School of Medicine and the affiliated VA Palo Alto Health Care System provide a highly stimulating and interactive research environment that includes a world renowned Cardiovascular Institute (http://med.stanford.edu/cvi.html) and the Palo Alto Epidemiology Research and Information Center (ERIC) for Genomics. In combination, these organizations provide exceptional opportunities for post-doctoral scholars to join highly structured training programs that include, but are not limited, to three National Institutes of Health T32 grants and the VA Big Data-Scientist Training Enhancement Program (BD-STEP). For candidates with MD degrees, the Stanford Center for Clinical and Translational Research and Education offers exceptional KL2 and TL1 clinical research training programs. More advanced postdocs with M.D., M.D./Ph.D. and Ph.D. degrees, may also benefit from the recently established Expanded Pilot PI waiver to apply for R01-type grants that require Principal Investigator status. Due to restrictions imposed by our funding sources, the ideal candidate will also either be a citizen or a permanent resident of the United States.
Mentorship/co-mentorship will be structured according to research interests and will include faculty primarily from the Departments of Medicine, Epidemiology, the Cardiovascular Institute and/or the Palo Alto Epidemiology Research and Information Center (ERIC) for Genomics. Close collaborators and potential co-mentors in this respect at Stanford include colleagues and co-investigators to projects listed above: Hua Tang, Jonathan Pritchard, Stephen Montgomery, and Manny Rivas. Furthermore, all projects are multi-institutional and provide abundant opportunities to collaborate and network with leading genomic researchers across North America and Europe that are not based at Stanford University and/or the Palo Alto VA.
- The ideal candidate will have acquired formal training during their doctoral studies in molecular epidemiology and/or related fields including genetic epidemiology, human genetics, biostatistics, bioinformatics, or computational biology.
- The ideal candidate should also be comfortable structuring, linking, and analyzing large datasets that include dense electronic health records as well as a variety of –omics data (e.g. human genotyping array data, whole genome sequencing data, RNA-sequencing data, methylation array data, plasma metabolomics, plasma proteomics, circulating micro-RNA, etc.).
- Holders of either PhD and/or MD degrees are welcomed to apply.
- Non US residents or non-US citizens are also welcomed to apply.
- Curriculum vitae (biographical sketch) that includes details on your education and training to date, Visa status (if applicable), your programming experience, a bibliography of any publications, and the names of 3 references.
- A brief personal statement describing research interests to be pursued during training at Stanford is also highly recommended.