University of Virginia Hiring for Research Scientist in Bioinformatics and Computational Genomics at Charlottesville, VA Full Time

The Department of Biochemistry and Molecular Genetics at the University of Virginia is looking to hire a Research Scientist. The Research Scientist will be responsible for working with the PI, Dr. Francine Garrett-Bakelman, and members in the lab to use integrative computational genomics approaches and to develop bioinformatics methods for studying epigenetics and transcriptional regulation in the blood cancer Acute Myeloid Leukemia. Projects will be performed in collaboration with basic and translational faculty at UVA and other academic institutions.

General Faculty Members whose primary responsibilities include teaching, research, professional practice, or clinical service without encompassing the full scope of responsibilities expected from tenure-track faculty positions (e.g., an academic general faculty member could have primary responsibilities for research with minimal or no responsibility for classroom instruction, or have primary responsibilities for teaching and/or clinical practice without research obligations).

Job responsibilities include:

1. conducting basic science research using existing and innovative computational biology approaches;

2. developing and maintaining bioinformatics tools used for computational biology research;

3. writing reports and manuscripts for peer-reviewed publications;

4. attending academic conferences (virtually and/or in-person) to present the research works;

5. mentoring and supervising trainees, including postdoctoral fellows, graduate and undergraduate students in the lab on computational biology research;

6. other research related work for the lab.

Minimum Requirement
Education: Ph.D. or terminal degree. ABD may be accepted.

Preferred Requirements

1. Ph.D. or equivalent degree in quantitative science such as bioinformatics, computational biology, computer science, statistics, applied mathematics, physics, genomics, data science, or a related field.

2. At least three-year research experience in computational epigenomics and high-throughput sequencing analyses.

3. At least 5 years of experience in R programming and 2 years in Python programming.

4. Working knowledge of molecular biology and genomics.

5. Strong academic communication skills and teamwork skills.

6. At least three first-author or senior-author publications in peer-reviewed journals in the related research field.

Physical Demands
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.

Application Instructions: Please apply through Workday and complete an application online. Include the following documents:

• A CV/resume

• A cover letter

• Contact information for 3 references

All documents can be loaded into the resume submission field, multiple documents can be submitted into this one field. Internal applicants must apply through their UVA Workday profile. Incomplete applications will not be considered.

For questions about the application process, please contact Rhiannon O’Coin, Senior Academic Recruiter. Before a formal offer of employment is extended, the selected candidate will undergo a background check per university policy.

The University of Virginia, including 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.