Working Title: Research Associate
Position Type: Professional Research Staff
Department: Center for Public Health Genomics
Posting Date: 12-14-2017
The Miller Laboratory at the University of Virginia (millerlab.org) seeks a highly motivated postdoctoral research associate with a background in a quantitative field to investigate the genetic basis of coronary artery disease and related complex diseases. Available projects include the integration of large-scale human genome-wide association and multi-omics datasets (e.g. bulk and single-cell RNA-seq, ATAC-seq, ChIP-seq) from normal and diseased environments. The primary goals of this work are to map causal regulatory networks, gene-environment interactions, and cell-specific mechanisms associated with cardiovascular diseases, ultimately to inform new treatment and prevention strategies. There will also be opportunities to discover and prioritize clinically relevant mutations identified from WGS of large-scale, well characterized cohorts and leverage longitudinal multi-omics datasets to classify patients and disease subtypes.
The candidate will have access to a broad range of population genetic and genomic datasets, computational resources, and will be exposed to a stimulating and multi-disciplinary environment in the Center for Public Health Genomics (CPHG) led by Dr. Stephen Rich. This work will involve close collaborations with members of the CPHG and the newly formed Data Science Institute led by Dr. Philip Bourne. The candidate will also benefit from strong collaborations with faculty members of the Robert M. Berne Cardiovascular Research Center led by Dr. Gary Owens, and with the Departments of Biomedical Engineering and Biochemistry and Molecular Genetics.
Candidates must have a PhD in a quantitative field (e.g. bioinformatics, statistics, engineering, physics, computer science, genetics, or related field) required in hand by appointment start date. Experience in either statistical or computational data analysis is preferred, including proficiency in R, python (or other scripting languages). Experience in machine learning or deep learning is preferred but not required. The successful candidate will also have a strong working knowledge of biomedical fields such as human genetics, molecular/cell biology, physiology etc. Excellent written and verbal communication skills are required, as is the ability to work in a cross-functional team.
To apply, visit https://jobs.virginia.edu and search on Posting Number 0622320. Complete a Candidate Profile on-line; attach a current CV, cover letter, statement of research interests, and contact information for three references. The position will remain open until filled.
For additional information about the position, please contact Dr. Clint L. Miller (clintm at virginia edu).
The University of Virginia is an equal opportunity/affirmative action employer. Women, minorities, veterans, and persons with disabilities are encouraged to apply.
E-mail a Friend: jobs.virginia.edu/applicants/Central?quickFind=83473