Postdoctoral Research Fellow - Multiomics and Causal Inference
Lead cutting-edge cardiovascular multiomics and causal inference research at the University of Michigan.
Best for:Best for quantitative researchers with a doctoral degree and strong R or Python skills interested in cardiovascular multiomics and causal inference.
Overview
The Division of Cardiovascular Medicine at the University of Michigan seeks a Postdoctoral Research Fellow to join an expanding, well-funded research program at the intersection of AI, advanced cardiac imaging, multiomics, and cardiometabolic disease. Working under the primary supervision of Dr. Venkatesh Murthy and in close collaboration with Dr. Sascha Goonewardena, the fellow will drive hypothesis-driven discovery focusing on coronary microvascular disease and conditions disproportionately affecting women. The role involves managing multi-omic analyses using established computational pipelines, executing causal inference studies on biobank-scale datasets, and preparing high-impact peer-reviewed publications. The appointment is structured as an annual renewable contract for up to three years, offering an exceptional environment for scientific leadership and professional development.
What you'll do
- Develop and apply analytical pipelines integrating high-throughput proteomic, metabolomic, genomic, and clinical data from large prospective cohort studies.
- Conduct causal and genetic inference studies, including Mendelian randomization and mediation analyses in biobank-scale datasets.
- Draft and prepare first-author manuscripts for submission to peer-reviewed scientific journals and present findings at academic conferences.
- Contribute to grant proposals, progress reports, and preliminary data generation for future funding opportunities.
- Engage actively in regular laboratory meetings, journal clubs, and collaborative scientific initiatives.
- Provide mentorship and guidance to junior research trainees within the program.
Requirements
Degree required: Doctoral degree (PhD, MD/PhD, or MD) in computational biology, bioinformatics, biostatistics, cardiovascular biology, epidemiology, or a closely related field
Language: English; professional fluency required for scientific writing and communication
Instruction: English
Publications: Track record of peer-reviewed publications relative to career stage is preferred
- Demonstrated research experience with proteomic, metabolomic, or other omic data analysis
- Proficiency in R and/or Python programming for statistical modeling and pipeline development
- Familiarity with causal inference or genetic epidemiology techniques such as Mendelian randomization
- Strong written and oral communication skills with a record of independent project execution
- Ability to work collaboratively within a multidisciplinary team of clinicians and data scientists
- Must hold a recognized doctoral degree (PhD, MD, or equivalent) prior to appointment
Funding & terms
How to apply
Deadline: 2026-11-12 · open until filled
Interested applicants should submit their application materials through the University of Michigan online career portal. Ensure all required documentation including a curriculum vitae and cover letter are uploaded as part of the submission.
- CV
- Cover letter
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