About Virginia Tech:
Virginia Tech is a public land-grant university, committed to teaching and learning, research, and outreach to the Commonwealth of Virginia, the nation, and the world. Building on its motto of Ut Prosim (that I may serve), Virginia Tech is dedicated to InclusiveVT—serving in the spirit of community, diversity, and excellence. We seek candidates who adopt and practice the Principles of Community, which are fundamental to our on-going efforts to increase access and inclusion, and to create a community that nurtures learning and growth for all of its members. Virginia Tech actively seeks a broad spectrum of candidates to join our community in preparing leaders for the world.
The Biocomplexity Institute of Virginia Tech (BI) broadly integrates disciplines – from molecular science to policy analysis – to address pressing challenges to human health, habitat, and well-being. We use an information biology approach to predict, explain, and visualize the behavior of massively interacting systems. The institute guides emergency response to epidemics, makes urban infrastructure more sustainable, and accelerates the discovery of treatments for chronic diseases.
BI is seeking an outstanding researcher to join our interdisciplinary team and contribute to a variety of projects involving the analysis, simulation, and interpretation of health data, especially infectious disease. The work will be in support of operational organizations in the federal government, the state and local public health department, and part of federally funded research sponsored by NIH & NSF. The candidate will work in the Network Dynamics and Simulation Science Laboratory (NDSSL) and have the opportunity to interact and collaborate within a diverse multidisciplinary team representing the fields of computer science, statistics, economics, physics, software engineering, and bioinformatics. The (Senior) Health Data Scientist will be expected to assist in the development of grant proposals and publications, and presenting findings at scientific meetings, as needed. Primary responsibilities will be assisting and leading multiple applied research projects using analysis and simulation to address public health policy questions.
This position will hold the faculty rank of either research associate or senior research associate according to candidate qualifications. For more information on the university faculty ranks, please review the faculty ranks for research faculty at http://provost.vt.edu/faculty_affairs/faculty_handbook/chapter06/chapter06.html
In accordance with university policy for non-student positions, this position will require a conviction check.
- MPH, M.S., or bachelor's degree with significant relevant professional experience, in Epidemiology, Biostatistics, Computational Biology, or other quantitative health field; or for rank of Senior Research Associate, PhD or MS with significant relevant professional experience in Epidemiology, Biostatistics, Computational Biology or other quantitative health field.
- Strong evidence of commitment to and understanding of biological/biomedical research, especially as it pertains to infectious diseases.
- Experience in analyzing population health data and interpreting its impact and use for answering policy and epidemic decision support questions.
- Demonstrable knowledge of scientific computing environments, e.g. unix, statistical analysis programs (R, Python, SAS, etc.),
- Strong communication skills and the ability to work effectively with other team members. For rank of Senior Research Associate, must have demonstrated experience leading an internal team (not necessarily in a supervisory role).
- Evidence of peer-reviewed scientific papers and other high quality writing.
- Evidence of successful participation in collaborative research projects. For rank of Senior Research Associate, must have demonstrated experience in leading a multi-group collaboration
- Ability to travel (domestically and/or internationally) to meet with collaborators, make conference presentations, and work with researchers.
- Familiarity with mathematical modeling of disease
- Strong ability to visualize complex datasets
- Familiarity with geospatial analyses
Employee Category: Research Faculty
Appointment Type: Restricted
Tenure Status: Non-Tenure Track
Percent Employment: Full-time
Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, gender, gender identity, gender expression, national origin, political affiliation, race, religion, sexual orientation, genetic information, or veteran status; or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees, or applicants; or any other basis protected by law.
For inquiries regarding non-discrimination policies, contact the executive director for Equity and Access at 540-231-2010 or Virginia Tech, North End Center, Suite 2300 (0318), 300 Turner St. NW, Blacksburg, VA 24061.
Review Date: 12/06/2016