Research Scientist or Sr Research Scientist in Bioinformatics/Computational Biology, The Robert M. Berne Cardiovascular Research Center

The Robert M. Berne Cardiovascular Research Center, at the University of Virginia, is seeking a Research Scientist or Sr Research Scientist in Bioinformatics/Computational Biology. The selected applicant will be part of a multidisciplinary team, developing integrative analysis and machine learning/AI computational pipelines and performing analyses in collaborative projects using human multi-omic immune cell data, advanced imaging, genetic and clinical data as well as data from mouse model systems.

Candidate will identify opportunities and implement solutions for managing, visualizing, analyzing, and interpreting genomic, proteomic, single cell and spatial transcriptomic data. The successful candidate will have a demonstrated ability to translate biological questions into technical design, and to identify, prioritize, and execute bioinformatics tasks to meet project goals and deadlines. They will participate in meetings and consultations with CVRC Researchers to discuss design and interpretation and will assist in manuscript and grant preparation. The candidate should have a passion for bioinformatics and enjoy collaborating and supporting academic researchers, attending seminars and meetings. The selected candidate will get an opportunity to master their bioinformatics skill set in a very close and interactive environment.

We seek a candidate that has strong communication skills and is a team player. A working knowledge of UNIX and scripting is important for this position. The ideal candidate is expected to have a good command of at least one language (C/C++ or R or Python). Knowledge of database development is a plus.

This will be an exciting environment, in which there will be opportunities to advance basic, translational, and precision medicine research as well as develop innovative, advanced computational and machine learning/AI methods with a team of computational biologists, computer scientists, and cardiovascular disease researchers.

Education :

Minimum: Ph.D. in Bioinformatics, Genomics, Biostatistics, or a related field

Experience :

Research Scientist
Terminal degree in a quantitative science including but not limited to Bioinformatics, Computer Science, Statistics, Data Science, Physics, Mathematics, Biophysics, Engineering, Chemistry or other related science fields with preference given to those with formal training in integrative and/or machine learning analysis of single cell and bulk RNAseq, mass cytometry, spatial transcriptomics, functional genomics, and biomedical data.
Candidates with experience in development of computational pipelines and large-scale data management are highly encouraged to apply.
1-3 years of experience with programming in Python and R with a strong background in UNIX is preferred. Student experience accepted.
Strong quantitative background including statistical and/or physical modeling, machine learning or computational biology experience (e.g., analysis of high throughput sequencing data and basic understanding of underlying algorithms/statistical models).
Experience with open-source software, tools, and databases for analyzing next-generation sequencing data (RNA-seq, ChIP-seq, DNA variation, epigenetics, microbiome, and metagenomics).
Excellent teamwork, communication and writing skills.
Knowledge of molecular and cellular biology concepts is also required.
Preference given to those with formal training in integrative and/or machine learning analysis of single cell and bulk RNAseq, mass cytometry, spatial transcriptomics, functional genomics, and biomedical data

Sr Research Scientist
Terminal degree in a quantitative science including but not limited to Bioinformatics, Computer Science, Statistics, Data Science, Physics, Mathematics, Biophysics, Engineering, Chemistry or other related science fields with preference given to those with formal training in integrative and/or machine learning analysis of single cell and bulk RNAseq, mass cytometry, spatial transcriptomics, functional genomics, and biomedical data.
Candidates with extensive experience in development of computational pipelines and large-scale data management are highly encouraged to apply.
A publication track record of bioinformatics and/or machine learning analysis of biomedical data is strongly preferred.
Minimum of 5 years of experience with programming in Python and R with a strong background in UNIX. Student experience accepted but prefer academic or industry experience.
Strong quantitative background including statistical and/or physical modeling, machine learning or computational biology experience (e.g., analysis of high throughput sequencing data and basic understanding of underlying algorithms/statistical models).
Experience with open-source software, tools, and databases for analyzing next-generation sequencing data (RNA-seq, ChIP-seq, DNA variation, epigenetics, microbiome, and metagenomics).
Excellent teamwork, communication and writing skills.
Knowledge of molecular and cellular biology concepts is also required.
Preference given to those with formal training in integrative and/or machine learning analysis of single cell and bulk RNAseq, mass cytometry, spatial transcriptomics, functional genomics, and biomedical data.

This is a restricted position; continuation is dependent on funding and satisfactory performance.

This position is located in Charlottesville, Virginia. This is a full-time benefited position. For more information on the benefits at UVA, visit www.hr.virginia.edu/benefits .

The anticipated hiring range is commensurate with education and experience. 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 apply through the UVA job board , and search for R0059744. Internal applicants must apply through their UVA Workday profile by searching 'Find Jobs'. Complete an application online with the following documents:
• CV/Resume
• 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.

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.

For questions about the application process, please contact Jon Freeman, Recruiting Specialist, at

For more information about UVA and the Charlottesville community, please see and .

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.

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.

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