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University of Michigan

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Postdoctoral Research Fellow in Multiomics and Causal Inference University of Michigan in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

The position is described as part of a nationally and internationally funded research program and is renewable annually for up to three years, contingent on satisfactory performance and continued funding. No stipend amount is stated.

Deadline

Nov 12, 2026

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Country

United States

University

University of Michigan

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Keywords

Computer Science
Biostatistics
Cardiology
Biology
Medical Science
Causal Inference
Salud Pública
Omics
Genomic
Statistics
Bioinformatic
Metabolomic

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About this position

Postdoctoral Research Fellow – Multiomics and Causal Inference at the University of Michigan (Ann Arbor, United States).

This postdoctoral opening sits within the Division of Cardiovascular Medicine / Michigan Medicine and focuses on multiomics, proteomics, metabolomics, genomics, bioinformatics, biostatistics, and causal inference. The program is led by Drs. Venkatesh Murthy and Sascha Goonewardena and aims to advance precision diagnostics and therapeutic discovery for coronary microvascular disease and other cardiometabolic conditions, with a particular emphasis on diseases affecting women.

The fellow will lead hypothesis-driven discovery work across omics and causal inference work streams, using analytical pipelines for high-throughput proteomic, metabolomic, genomic, and clinical datasets. Responsibilities include multi-omic analysis, Mendelian randomization, mediation analysis, manuscript preparation, presentations at scientific meetings, and contributions to grants, reports, and mentoring.

Eligibility highlights include a doctoral degree (PhD, MD/PhD, or MD) in computational biology, bioinformatics, biostatistics, cardiovascular biology, epidemiology, or a closely related field; experience with omic data analysis; strong R and/or Python skills; and familiarity with causal inference or genetic epidemiology methods. Preferred experience includes large cohort or biobank datasets, Olink or SomaScan, cardiovascular biology, multi-omic integration, and HPC/cloud computing.

The appointment is annual and renewable for up to three years, subject to performance and continued funding. The role is onsite in Ann Arbor, Michigan. Apply via the University of Michigan careers portal; the posting indicates review may begin after the minimum posting period and the position may close once filled.

Funding details

The position is described as part of a nationally and internationally funded research program and is renewable annually for up to three years, contingent on satisfactory performance and continued funding. No stipend amount is stated.

What's required

Doctoral degree (PhD, MD/PhD, or MD) in computational biology, bioinformatics, biostatistics, cardiovascular biology, epidemiology, or a closely related field. Applicants should have experience analyzing proteomic, metabolomic, or other omic data in a research context, proficiency in R and/or Python, familiarity with causal inference or genetic epidemiology methods such as Mendelian randomization and mediation analysis, strong scientific writing and oral communication skills, and the ability to drive projects independently. Preferred experience includes large cohort or biobank datasets, Olink or SomaScan platforms, cardiovascular or cardiometabolic disease background, multi-omic integration, and HPC/cloud computing.

How to apply

Apply through the University of Michigan careers posting using the Apply Now link. Review begins after the minimum posting period and the opening may be removed once filled.

More information can be found here

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