Faculty Searches Fall 2020 - Assistant Professor

The Department of Statistics at the University of Virginia (UVa) College and Graduate School of Arts & Sciences invites applicants for a tenure-track faculty position, Assistant Professor.  All research areas in Statistics are considered.  The Department is experiencing increased student demand in both statistics and computing, so we welcome those whose research and teaching span statistical methodology, large-scale inference, and computational sciences. The appointment  begins with Fall term of 2020.  In addition to developing external funding to support research endeavors, candidates will be expected to teach at the graduate and undergraduate levels, advise Ph.D. students, and provide service to the university, department and professional organizations.

The Department of Statistics at UVa was established in 1989 and currently has 17 research & teaching faculty. The Department works closely with the Biostatistics Department at the Medical School, Quantitative Collaborative (Social Sciences), the newly created School of Data Science, and other departments and schools. Faculty interests range from theoretical to applied statistics (including statistics in the social, medical, and physical sciences), and we supervise a growing number of students at all levels. The department offers the Bachelor of Arts, Master of Science, and Ph.D. degrees in Statistics.

 

Qualifications:
Applicants must be on track to receive a Ph.D. in Statistics, Biostatistics, Computer Science, or a related field by May 2020 and must hold a PhD at the time of appointment.

Application Process:
Please apply online at https://uva.wd1.myworkdayjobs.com/en-US/UVAJobs/job/Charlottesville-VA/Assistant-Professor-of-Statistics_R0010727-1  and attach a cover letter, CV, Statement describing research agenda, Statement of teaching philosophy and experience, and Contact Information for at least 3 references. The cover letter should include areas of research/scholarship interest; potential collaborations/projects at UVA; and demonstrated past experience working on issues of diversity, equity and inclusion and/or working with diverse populations.

 

Application Deadline:
Review of applications will begin December 2, 2019; candidates who apply by then will be given priority consideration, but the position will remain open until filled.

For questions regarding the position or application process contact, Rich Haverstrom, Faculty Search Adviser, at rkh6j@virginia.edu.

For questions regarding the position in the Statistics department, please contact Karen Kafadar, Search Committee Chair, at kk3ab@virginia.edu.

Centrally located in Virginia, Charlottesville boasts a thriving intellectual community and cultural life, with easy access to recreational venues and convenient travel to Richmond, Washington D.C. and SAMSI, which combine to make UVa a most desirable place to live and work. For more information about UVA and the area, please visit http://uvacharge.virginia.edu/guide.html.
For information on the benefits available to members of the academic faculty at UVA, visit hr.virginia.edu/benefits.

UVA assists faculty spouses and partners seeking employment in the Charlottesville area.  To learn more please visit https://dualcareer.virginia.edu/  For more information about UVA and the Charlottesville community please see http://www.virginia.edu/life/charlottesville and https://embarkcva.com/.

The University of Virginia, including the UVA Health System and the University Physician’s Group 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, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.