Rust Job: Bioinformatician

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Charlottesville, VA - United States of America

Job type


Rust Job Details


The Department of Public Health Sciences at the University of Virginia seeks Bioinformaticians for two openings in a computational biology research group led by Nathan Sheffield

The Bioinformaticians 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 bioinformaticians 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.
About the Lab:
The Databio group 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 Cente r 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 .

Minimum Qualifications:
  • Education: Bachelor's degree in Bioinformatics, Computational Biology, Computer Science, Computer Engineering, or a related discipline
  • Experience: 5 years
Preferred Qualifications:
  • Experience and understanding of genome biology
  • Skill with Rust and object-oriented programming
  • Experience or interest in machine learning approaches used in natural language processing
  • Computational experience with scripting in R or Python
  • A willingness to contribute to team projects (such as building communal software) and demonstrated commitment to sharing software and data with the community.
  • Experience with git and GitHub
Anticipated Hiring Range:
$45,000 - 90,000 based on education and experience.

Physical Demands:
This position is located in Charlottesville, VA.This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.

This position is a restricted position and is dependent upon project need, availability of funding and performance. This is an Exempt level, benefited position. For more information on the benefits at UVA, visit .

This position will remain open until filled. 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.

References will be completed via UVA's standardized process Skill Survey. A total of five references will be requested via SkillSurvey during the final phase of the interview process.

To Apply:
Please apply through Workday , and search forR0053659.
Internal applicants must apply through their UVA Workday profile by searching 'Find Jobs'
Complete an application online with the following documents:
  • CV
  • Cover letter
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.

For questions about the application process, please contact Yelena Markazyan, Academic Recruiter at ym

For more information about UVA and the Charlottesville community please see and ;br>
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.