Open Rank Tenure/Tenure Track Biomedical Data Science Faculty
Working Title: Open Rank Tenure/Tenure Track Biomedical Data Science Faculty
Position Type: Teaching and Research Faculty
Department: Dean's Office, School of Eng and Applied Science
Posting Date: 12-04-2017
The University of Virginia (UVA) seeks exceptional applicants for tenure-track or tenured faculty appointments in the broad area of Biomedical Data Science. Primary appointments will be in the School of Engineering and Applied Science (SEAS) or School of Medicine (SOM)); secondary appointments are available in departments associated with SEAS, SOM and the Data Science Institute (DSI). Candidates are expected to build and sustain rapidly-growing, highly-visible research programs at the confluence of any area of Biomedicine and Data Science. Candidates with strong backgrounds in areas of data science such as: machine learning; data visualization; data integration and engineering; data acquisition and dissemination; and data ethics, law, policy and social implications are encouraged to apply. Candidates also must have expertise in one or more areas of bioscience including, but not limited to, omics technologies, imaging, large scale and predictive modeling, precision medicine, immunology or neuroscience.
UVA is proud to have a strong culture of collaboration and collegiality and is committed to creating collaborative and diverse environments necessary to solve the next generation of research challenges. Successful candidates will help build bridges and be engaged in cross-disciplinary research between SEAS, SOM and DSI; teach and advise students at the undergraduate and graduate levels; and perform service to the institution and the profession, locally, nationally and internationally. Rank is contingent upon experience.
A Ph.D. and/or M.D. in a relevant field is required. A commitment to teaching excellence is essential, as is evidence of an explicit commitment to diversity and of advancing understanding and outcomes for underrepresented groups. For a tenure-track appointment, an established or potential high-impact publication record, accompanied by potential for extramural funding in the areas of interest outlined above, are required. For an appointment with tenure, the applicant must have a rapidly emerging or established national reputation, a documented line of research related to the areas of interest outlined above, and a track record of existing and sustained extramural funding.
To apply, visit http://jobs.virginia.edu and search for Posting 0622246. Complete a Candidate Profile online and attach a cover letter, curriculum vitae, statement of teaching philosophy, statement of research interest, and contact information for at least three references. Applicant review will begin January 4, 2018. The position remains open to candidates until filled.
For questions about the position, please contact Prof. Philip Bourne via email at email@example.com. For questions about the application process, please contact Ellen Beverly at firstname.lastname@example.org.
UVA assists faculty spouses and partners seeking employment in the Charlottesville area. To learn more about these services, please visit http://provost.virginia.edu/dual-career. For more information about UVA and the surrounding area, please visit http://uvacharge.virginia.edu/guide.html.
With one of the highest graduation rates of minority undergraduate students and one of the highest percentages of women engineering students among public universities, the University of Virginia is fundamentally committed to increasing the diversity of its faculty and staff. UVA is an affirmative action and equal opportunity employer. We seek out nominations of and applications from women, members of minority groups, veterans, individuals with disabilities, and others who would bring additional dimensions of diversity to the university's research and teaching mission. We believe that diverse opinions and experiences enrich and strengthen our academic and local community.
E-mail a Friend: jobs.virginia.edu/applicants/Central?quickFind=83384