About the lab

The Databio group (http://www.databio.org) is an interdisciplinary and collaborative computational biology research group located in the Center for Public Health Genomics at UVA. We are also affiliated with the Department of Biomedical Engineering, Department of Biochemistry and Molecular Genetics, Department of Public Health Sciences, the School of Data Science, the Cancer Center, and the Child Health Research Center at UVA.

Our research is at the interface of computation and biology, drawing on techniques in computer science, data science, bioinformatics, and machine learning, and applying them to biological questions in cancer, epigenetics, single-cell analysis, development, and genomics. We collect both novel data and public data and make use of UVA’s high-performance cluster for computational approaches to biological questions.

Our biological questions are focused on understanding gene regulation and epigenetics in development and disease, such as cancer, atherosclerosis, and kidney disease. How does DNA encode regulatory networks that enable cellular differentiation? We rely on experimental data from sequencing-based epigenome experiments like ATAC-seq, bisulfite-seq, and ChIP-seq, and we use these data to study fundamental principles of regulatory DNA in human health.

We are building a team of intelligent, creative people who are interested in working together to accomplish great things. We collaborate extensively. We emphasize social coding, using GitHub to share code both within the group and so others can benefit from our work. We seek to write readable, reusable code and apply it to new biological questions. We challenge the norm in academic computational research of individual scientists writing isolated code, and instead push open, multi-author code development. If these topics excite you, please read more about our research interests, recent publications, and philosophy of open data.

About the university

The University of Virginia, founded by Thomas Jefferson in 1819, is the only collegiate UNESCO World Heritage site in the US. It located near Shenandoah National Park in the beautiful foothills of the Appalachian Mountains in Charlottesville, Virginia. UVA routinely ranks in the top 3 public universities in the United States, with a co-located School of Medicine and a top-tier environment for research. Charlottesville is also a great place to live. If you’re unfamiliar with area, please read the many reasons you should consider coming to UVA.

Job description

The bioinformatician will help support medical research with large-scale multi-omic data processing and software development using a tech stack that includes Python, R, Rust, PostgreSQL, Docker, AWS, Azure, React, Bioconductor, FastAPI, and NodeJS. They are expected to help with processing biological data, as well as to build new tools to make this easier to do.

The bioinformatician have two primary responsibilities:

Curating biomedical research data, including using manual and AI-assisted approaches to standardize metadata, documenting data, and processing data through computational pipelines using supercomputing resources (SLURM). The will contribute to developing and deploying new data resources for use by our lab and external users.
Contributing to biomedical research projects. The bioinformaticians will be responsible for performing data analysis on multi-omic research data, such as ATAC-seq, DNA methylation, or RNA-seq data, for a variety of research questions in human health. They will also develop new methods and tools to facilitate this research.

Interested in joining?

For this position, you should have some interest in either building bioinformatics applications or analyzing large biomedical datasets.

Required qualifications:

Bachelor’s degree in Bioinformatics, Computational Biology, Computer Science, Computer Engineering, or a related discipline and at least 1 year of related experience OR an equivalent combination of experience, education, and certifications.
Computational experience with scripting in R or Python
Experience with git and GitHub
A willingness to contribute to team projects (such as building communal software) and demonstrated commitment to sharing software and data with the community.

Preferred qualifications:

Skill with Rust and object-oriented programming.
Experience or interest in machine learning approaches used in natural language processing

Include with your application:

Your education and publication history, if any
Your career goals, and what you think you would gain from experience in our group
Why you think you would fit well, and what you would contribute
Your biggest ideas for what projects or types of projects you find exciting
A link to GitHub or other public repository with code you showcase, if any

The University of Virginia is an equal opportunity and affirmative action employer. Applications will be reviewed on a rolling basis and the position will remain open until filled.

Informal inquiries and application materials can be directed to the attention of Dr. Nathan Sheffield at . But ultimately, official applications must be submitted at the official UVA application system.