The Miller Laboratory at the University of Virginia (millerlab.org) seeks a talented postdoctoral research associate with a background in the life sciences or a quantitative field to apply systems genomics approaches to investigate mechanisms of inherited vascular diseases. Available projects include the generation and analysis of single-nucleus (e.g., snATAC/snRNA-seq, scCUT&Tag), and spatial (e.g., spatial transcriptomics, proteomics) datasets from healthy and diseased subjects of ancestrally diverse backgrounds. The candidate will also contribute to genomic perturbation based functional screens to validate these discoveries in cell models. The overall goals of this work are to contextualize rare and common genetic variation associated with cardiovascular diseases to inform early-stage detection and prevention. There will also be opportunities to classify common disease subtypes using machine learning approaches and identify clinically relevant drug targets/biomarkers for vascular diseases.

The Research Associate will have access to a broad range of population genetic and genomic datasets through consortia projects (e.g., TOPMed, CHARGE, MESA, Leducq PlaqOmics and Chan Zuckerberg Initiative), high performance computing resources, and will be exposed to a stimulating, multi-disciplinary and inclusive environment in the Center for Public Health Genomics (CPHG). This work will involve close collaborations with other CPHG labs to broaden training in highly desirable wet lab and computational biology skills. The candidate will also benefit from strong collaborations with faculty members in the Cardiovascular Research Center and Departments of Biomedical Engineering and Biochemistry and Molecular Genetics. 

Qualifications:

• PhD in a life sciences or quantitative field (required in hand by appointment start date).

• Strong working knowledge of biomedical fields such as human genetics, molecular/cell biology, physiology etc.

• Excellent written and verbal communication skills

• Ability to work in a cross-functional team

• Experience in statistics or genetics is preferred, including proficiency in R, python (or other scripting languages).

As the project progresses, there will be ample opportunities to present in national and international scientific meetings. The candidate will also be strongly encouraged to apply for internal and external grant and fellowship opportunities.

The University will perform background checks on all new hires prior to employment. A completed pre-employment health screen is required for this position prior to employment.   

TO APPLY:

Please visit UVA job board: https://uva.wd1.myworkdayjobs.com/UVAJobs and search for R0043627

Complete an application online and attach:

• CV
• Research Statement
• Contact information for 3 references

PROCESS FOR INTERNAL UVA APPLICANTS: Please apply through your Workday Home page, search “Find Jobs”, and search for R0043627

For questions about the application process, please contact Rhiannon O’Coin, Senior Academic Recruiter, rmo2r@virginia.edu .

To learn more about the position and the research please contact Dr.Clint Miller, clintm@virginia.edu

Upload all materials into the resume submission field, multiple documents can be submitted into this one field. Alternatively, merge all documents into one PDF for submission.

Applications that do not contain all required documents will not receive full consideration. 

PHYSICAL DEMANDS

 This position can spend extensive periods of time standing and squatting while conducting experiments or caring for animals. Also requires keyboarding and other bench work and animal procedures requiring finer finger manipulation.

COVID Vaccination Requirement and Guidelines

Please visit the UVA COVID-19 Job Requirements and Guidelines  webpage prior to applying for current information regarding vaccination requirements?and?guidelines for employment at UVA.

The University of Virginia, i ncluding the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician’s Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff.  We believe diversity is excellence expressing itself through every person's perspectives and lived experiences.  We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.