Assistant Professor of Research in Genome Sciences
Join the University of Virginia as a Research Assistant Professor focusing on genetic and multi-omics data integration for cardiovascular disease research.
Best for:Best for quantitative researchers and bioinformaticians with a strong background in human genetics, genomics, and multi-omics data analysis.
Overview
The Department of Genome Sciences at the University of Virginia invites applications for a Research Support Assistant Professor position within the laboratory of Dr. Ani Manichaikul. The successful candidate will lead and contribute to statistical and bioinformatic projects integrating whole genome sequencing with transcriptomic, proteomic, and other 'omics datasets. The work aims to discover novel genes and biological pathways underlying coronary artery disease, cardiomyopathy, and heart failure using large multi-center human cohorts. Applicants will also have opportunities to mentor junior lab members and undergraduate students while working in a collaborative research environment.
What you'll do
- Conduct statistical and bioinformatic analyses of whole genome sequencing data for large multi-center cohort and case-control studies
- Analyze genome-wide association study (GWAS) summary statistics and large-scale genetic datasets
- Process and analyze bulk and single-cell transcriptomic datasets alongside proteomic and other molecular 'omics data
- Perform integrative systems genetics analyses to identify novel genes and biological pathways linked to heart disease
- Collaborate with multidisciplinary research teams on cutting-edge human genetics and genomics projects
- Engage in mentoring and supporting junior laboratory members, staff, and undergraduate students
Requirements
Degree required: PhD or equivalent degree in genetics, statistics, biology, biostatistics, bioinformatics, computational biology, data science, or a related quantitative field
Language: English
Instruction: English
- Extensive experience in analyzing whole genome sequencing or high-throughput molecular 'omics data
- Proficiency in statistical genetics, bioinformatics, or computational biology methods
- Demonstrated ability to work collaboratively within multidisciplinary research teams
- At least 3 years of relevant post-doctoral or professional research experience
- Completion of a PhD or equivalent degree in a relevant quantitative or biological science discipline
- Minimum of 3 years of relevant research experience following the completion of the PhD degree
Funding & terms
How to apply
Interested applicants should submit their application materials through the designated external job portal link provided in the posting.
- CV
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.