Postdoctoral Research Associate

About the role

The Department of Genome Sciences at the University of Virginia is seeking a Postdoctoral Research Associate to join the Miller Lab and contribute to the Leducq COMET Network.

Responsibilities

• Develop and apply advanced computational approaches to identify disease-associated genes, pathways, cell states, and regulatory mechanisms involved in vascular calcification, atherosclerosis, and broader cardiovascular disease.
• Build, benchmark, and maintain robust bioinformatics pipelines for data processing, quality control, integration, visualization, and reproducible analysis.
• Use machine learning and statistical approaches to identify disease-associated genes, pathways, regulatory programs, cell states, and molecular mechanisms.
• Integrate human genetics, functional genomics, and multi-omic datasets to prioritize candidate genes and causal pathways involved in vascular calcification and cardiovascular disease.
• Contribute to the development of scalable computational pipelines, machine learning workflows, and integrative analyses that enable mechanistic discovery across diverse genomic and multi-omic datasets.
• Work closely with lab members and Leducq COMET Network collaborators to harmonize datasets, refine analysis strategies, and interpret findings in a biological and clinical context.
• Present progress in weekly group meetings and monthly consortium meetings.
• Draft manuscripts, contribute to grant applications, and support dissemination of findings through publications and presentations at national and international conferences.
• Contribute to the training and mentorship of junior lab members, including graduate students, undergraduate researchers, and computational trainees.

Requirements

• PhD degree in bioinformatics, computational biology, genomics, genetics, biostatistics, statistics, computer science, biomedical engineering, systems biology, or a related quantitative discipline.
• Strong programming skills in R and Python.
• Experience working in Linux/Unix environments and using bash, high-performance computing systems, and reproducible computational workflows.
• Experience analyzing large-scale genomic or multi-omic datasets.
• Familiarity with workflow management systems such as Nextflow.
• Strong understanding of statistical analysis, data visualization, and reproducible research practices.
• Excellent written and oral communication skills.
• Demonstrated ability to work both independently and as part of a collaborative, cross-functional team.

Preferred Qualifications

• Experience with single-cell RNA-seq, single-cell ATAC-seq, spatial transcriptomics, epigenomics, proteomics, or other high-dimensional omics datasets.
• Familiarity with cardiovascular biology, vascular disease, vascular calcification, atherosclerosis, or related disease areas.
• Experience with machine learning frameworks and workflows, including PyTorch, scikit-learn, and standard supervised and unsupervised learning approaches.
• Experience developing, containerizing, and documenting reusable computational pipelines.
• Familiarity with version control, package development, cloud or HPC deployment, and collaborative coding practices.
• Prior experience contributing to manuscripts, grants, consortium projects, or large collaborative research efforts.

Benefits

Salary range: $50,000 - $70,000 yearly, commensurate with education and experience.

Schedule

This is a 12-month appointment with the possibility of renewal contingent upon satisfactory performance and the availability of funding.

Pay

This position is based in Charlottesville, VA, and must be performed fully on-site.