Postdoctoral Research Associate, Department of Genome Sciences

University of Virginia

1d • Onsite

About The Position

The Department of Genome Sciences at the University of Virginia (UVA) invites applications for a Postdoctoral Research Associate position in the broad areas of biostatistics, data science, and AI. This position will focus on developing and applying novel statistical methods, machine learning approaches, and AI-driven computational tools, with a strong focus on statistical genetics and genomics. Methodological work will be closely linked to applications in cancer and/or autism research. The fellow will work under the supervision of Dr. Ziqiao Wang and there will be opportunities to collaborate with the School of Data Science, Department of Statistics, and UVA Comprehensive Cancer Center.
Research directions include but are not limited to: multi-omics data integration, polygenic risk score analysis, modeling of gene–environment interactions, and Mendelian randomization studies for causal inference. Additional information on research projects and recent publications can be found on the lab’s website (https://ziqiaow.github.io).
Postdoctoral employment is temporary and is normally limited to an individual who has been awarded a Ph.D. or equivalent doctorate within the previous five years and who will be involved in full-time research or scholarship at the University. Employment as a Postdoctoral Research Associate is viewed as training and is preparatory for a full-time academic or research career, is supervised by a senior scholar, and allows the appointee to publish the results of his/her research or scholarship during the training period.

Requirements

• Doctoral degree in Biostatistics, Statistics, Computer Science, Data Science, Bioinformatics, or a related quantitative field

Nice To Haves

• Proficiency in statistical computing (e.g., R, Python)
• Strong quantitative skills (e.g., statistical methods, machine learning, etc.), the ability to manage large datasets, and experience with using large-scale datasets such as UK Biobank, All of Us, ARIC, TCGA is highly desirable
• A collaborative mindset and commitment to impactful research

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree