Statistics Jobs

This is a current listing of job announcements related to Statistics. To submit a job for posting please use the Statistics Job Submission Form. Please note that jobs are posted within 24hrs of submission. If you have any questions, comments, or need to make a correction regarding your job announcement, please contact jobs@stat.ufl.edu.

Position TitleOpen Rank

Company Information

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.

Duties and Responsibilities

The Virginia Tech Department of Statistics (www.stat.vt.edu) invites applications for a tenure track faculty position in Statistics to begin in August 2020. Appointment at the rank of assistant professor is preferred, but the level of associate or full professor will be considered for exceptional candidates. Requirements include a Ph.D. in statistics or a closely related field and a research focus in any of the following areas:data analytics, statistical/machine learning, artificial intelligence, cyber analytics, data mining, stochastic modeling/inference, or any related branch of computationally intensive statistical methods.

This position is part of a major emphasis on statistics at Virginia Tech, including computational modeling, data science and analytics, and empirical decision making. This search is targeting individuals who would teach in both the Department of Statistics and the Computational Modeling and Data Analytics (CMDA) program (https://www.ais.science.vt.edu/cmda.html). CMDA is a multi-department effort (together with Mathematics and Computer Science) to educate modern quantitative scientists by developing their knowledge base and skillset in computationally intensive techniques for modeling and inference.

Applications from researchers whose work and goals straddle traditional academic boundaries are especially encouraged. The successful applicant will also have the opportunity to be a key player in the development of the university’s “Data Analytics and Decision Sciences” destination area (https://www.provost.vt.edu/destination_areas/areas_of_focus/da_dd.html) and Virginia’s Cyber Initiative: (https://vtnews.vt.edu/articles/2018/06/cyber-initiative.html

Expectations for this position include: developing and maintaining a visible and vigorous funded research program; providing effective instruction and advising to a diverse population of undergraduate and graduate students; continuing development of professional capabilities and scholarly activities; curriculum development; participation in department, academy, college, and university governance; and professional service. The faculty handbook (https://www.provost.vt.edu/who_we_are/faculty_affairs/faculty_handbook.html) provides a complete description of faculty responsibilities.

Position Qualifications

Applicants must have a strong background in statistics with specialization in data analytics, machine learning, data mining, stochastic modeling/inference, interactive data visualization, high performance computing or computationally intensive statistical methods; a strong promise for developing a well-funded and distinguished research program; demonstrated experience with and commitment to interdisciplinary research; willingness to cross disciplinary boundaries to tackle complex scientific challenges; a desire to advise and teach a student body that is diverse with respect to socio-economic status, demographics, interests, and abilities; and commitment/sensitivity to address issues of diversity in the university community. Applicants must have earned a doctorate in a relevant discipline at the time of appointment.

Preference will be given to candidates with demonstrated interest in interdisciplinary scholarship employing statistical and data analytical techniques. Preference will also be given to assistant professor candidates, candidates with postdoctoral or similar experience, and candidates with a record of achievement as might be demonstrated during a postdoctoral or similar appointment.