Postdoctoral Research Fellow - Multiomics and Causal Inference

Postdoctoral Research Fellow - Multiomics and Causal Inference

We, the staff and faculty of the U-M Cardiovascular Center (CVC) team, are committed to advancing medicine and serving humanity through living and teaching our core values of Respect and Compassion;
Collaboration;
Innovation; and Commitment to Excellence. Each CVC employee is expected to understand and demonstrate that in every interaction we represent our entire organization in the care we provide and in the courtesies we extend to patients, families, and each respective team member. The CVC is dedicated to partnering with patients and families to deliver the safest and highest quality of health care.

The Division of Cardiovascular Medicine is firmly committed to advancing inclusion, diversity, equity, accessibility, and belonging, which are core to the culture and values of the Medical School Office of Research. Our community supports recruiting and cultivating a diverse workforce as a reflection of our commitment to serve the diverse people of Michigan and the world. We strive to create a work culture where each team member feels respected, valued, and safe.

Michigan Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally.

Our mission is guided by our Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society.

The Division of Cardiovascular Medicine at the University of Michigan is expanding a nationally and internationally funded research program at the cutting edge of cardiovascular medicine. Led by Drs. Venkatesh Murthy and Sascha Goonewardena - whose work has appeared in leading journals including NEJM AI, JAMA, and Circulation - the program fuses artificial intelligence, advanced cardiac imaging, multiomics (proteomics, metabolomics, and genomics), and cardiometabolic disease biology to develop precision diagnostics and identify novel therapeutic approaches, with a particular focus on coronary microvascular disease and other cardiovascular conditions that disproportionately affect women and remain poorly served by existing diagnostic tools.

This is a rare opportunity to join a high-impact, well-funded program doing science that matters.

This postdoctoral position offers an exceptional opportunity for a highly motivated researcher to lead the hypothesis-driven discovery work of the program's omics and causal inference work streams, under the primary supervision of Dr. Murthy, with close collaboration with Dr. Goonewardena and a broad network of national and international research partners. The fellow will lead multi-omic analyses using pipelines built by the program's computational team, drive causal inference studies in biobank-scale datasets, and translate findings into first-author publications.

This role emphasizes scientific leadership, discovery, and manuscript development. Appointments are made on an annual basis and are renewable, with a maximum total duration of three years, contingent on satisfactory performance and continued funding.

• Develop and apply analytical pipelines integrating high-throughput proteomic data with metabolomic, genomic, and clinical datasets from large prospective cohort studies to identify biological signatures of coronary microvascular disease and cardiometabolic disease
• Perform causal and genetic inference analyses - including Mendelian randomization and mediation analysis - in biobank-scale datasets
• Prepare first-author manuscripts for peer-reviewed journals and present work at national and international scientific meetings
• Contribute to grant applications, progress reports, and preliminary data generation for future funding
• Participate in laboratory meetings, journal clubs, and collaborative program activities
• Contribute to mentoring of junior trainees
• Other duties as assigned

• Doctoral degree (PhD, MD/PhD, or MD) in computational biology, bioinformatics, biostatistics, cardiovascular biology, epidemiology, or a closely related field
• Experience with proteomic, metabolomic, or other omic data analysis in a research context
• Proficiency in R and/or Python for statistical analysis and pipeline development
• Familiarity with causal inference or genetic epidemiology methods (e.g., Mendelian randomization, mediation analysis)
• Strong scientific writing and oral communication skills
• Demonstrated ability to drive projects to completion independently

• Experience with large prospective cohort or biobank datasets (CARDIA, MESA, Framingham Heart Study, UK Biobank, or similar)
• Experience with high-throughput proteomic platforms (Olink or Soma Scan)
• Background in cardiovascular biology, vascular biology, or cardiometabolic disease
• Track record of peer-reviewed publications…