Important Info
Please forward your application materials to Dr. Assimes (tassimes@stanford.edu). He will carefully review each application and respond promptly to those that are competitive and a good match for ongoing or soon-to-be-launched research projects, as well as the lab's existing expertise.
While we appreciate every application, the high volume of interest means we can only follow up with those whose backgrounds match our current project needs. If you haven't heard back within two weeks, thank you for your understanding that we are not able to move forward with your application.
Postdoctoral Scholar — Molecular Epidemiology and Integrative Multi-Omics of Cardiovascular Disease
Dr. Themistocles (Tim) Assimes, MD, PhD, FAHA, Professor of Medicine, is seeking up to two highly motivated and accomplished postdoctoral scholars to join his team of investigators in the Division of Cardiovascular Medicine – Department of Medicine, at Stanford University School of Medicine, Stanford, California, and the Stanford-affiliated VA Palo Alto Health Care System.
A successful applicant will be immersed in cutting-edge molecular epidemiology studies of traits related to cardiovascular disease using large-scale population biobanks including but not limited to the Million Veteran Program (>1.1M), the Women’s Health Initiative (>140k), All of US (>747k), 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, as well as 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 but are not limited to the following projects:
- Genetics of Cardiometabolic Diseases in the Veteran Affairs Population (I01 BX003362)
- Using genetic variation to study biology of blood lipids & coronary heart disease (R01HL127564)
- Intersecting clinical, genomic, and experimental investigation to understand the mechanisms and impact of coronary artery patterning (R01HL171326)
- Understanding how food & gene interactions impact LDL-C and drive variability in dietary responses (R01HL188164)
- Asian American Prevention Research: A Populomics Epidemiology Cohort (ARISE) (UH3HL169648)
- CARDIoGRAMplusC4D Consortium
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 and the Palo Alto Epidemiology Research and Information Center (ERIC) for Genomics. Together, these organizations offer exceptional opportunities for postdoctoral scholars to join highly structured training programs that include, but are not limited to, multiple National Institutes of Health T32 grants based at Stanford and the VA Big Data-Scientist Training Enhancement Program (BD-STEP).
For more senior postdoctoral candidates with MD degrees who may be competitive for an instructor position at the end of their training at Stanford, the School of Medicine offers the K12 Mentored Career Development Program, which provides didactic training, mentoring, and career development to prepare junior faculty for independent careers in translational research. More advanced postdocs with MD, MD/PhD, and PhD degrees, as well as instructors, may also benefit from the Expanded Pilot PI waiver process to apply for R01-type grants that require Principal Investigator status.
Mentorship/co-mentorship will be structured according to research interests and will include faculty primarily from the Departments of Medicine and of Epidemiology & Population Health, the Cardiovascular Institute and/or the Palo Alto Epidemiology Research and Information Center (ERIC) for Genomics. Furthermore, most projects are multi-institutional and provide abundant opportunities to collaborate and network with leading genomic researchers across North America and Europe who 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, computational biology, or phenomics (including EHR, deep medical imaging, and biomarker profiling).
- Experience applying machine learning or AI methods in these fields is an advantage.
- 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 microRNA, etc.).
- Please note that this position has no wet-lab component. Applicants holding a PhD, MD, or MD/PhD are welcome to apply.
- Non-US citizens and non-US residents are also welcome to apply.
Please submit your curriculum vitae (biographical sketch) that includes details on your education and training to date, your programming experience, a bibliography of any publications, the names and titles of 2 to 3 references, and Visa status (if applicable). A brief personal statement describing the research interests you would pursue during training at Stanford is also highly recommended.