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Assistant Collegiate Professor

The Department of Statistics at Virginia Tech ( seeks applicants for an Assistant Collegiate Professor (non tenure-track) position. This position is part of a major emphasis on statistics, computational modeling, data science, and decision making at Virginia Tech. This new faculty member will have the opportunity to be a key player  in the university’s “Data Analytics and Decision Sciences” destination area and to teach in the Computational Modeling and Data Analytics program (,   Virginia Tech’s data science undergraduate degree.

The Collegiate Faculty position is a non-tenure position with ranks at the Assistant, Associate, and Full Collegiate Professor levels that offer 3-, 5-, and 7-year renewable appointments, respectively. This position offers a clear path to promotion with increasingly longer contracts and promotion criteria clearly defined by College of Science and University guidelines. Collegiate Faculty participate in the College’s missions for excellence in education, scholarship, service, and commitment to diversity, equity and inclusion. For details on this track, see .

We seek candidates who are passionate about teaching statistics to undergraduate and graduate students.  Responsibilities of this Collegiate Faculty position will include teaching three courses per semester, where successful candidates will:

  • make contributions to our instruction in statistics, which includes computationally-intensive and massive data methods, as well as data science more broadly;
  • coordinate introductory and service courses, work closely with our undergraduate students, and engage in a variety of growing statistics and interdisciplinary curricula across the university;
  • continue to develop professional capabilities and participate in scholarly activities, including travel to and participation in professional conferences and societies; and,
  • participate in department, college, and university service, as well as professional service.

Required Qualifications

A successful candidate for this position must have a Ph.D. in statistics, biostatistics,  mathematics, computer science, or a related field and will be passionate about teaching undergraduate students in an inclusive and integrated environment. In addition, applicants should have a strong background in the application of statistics, and demonstrated research accomplishments that include journal publications and conference presentations.

Preferred Qualifications

Desirable characteristics we seek include a record of pedagogical achievement and vision, creativity, and leadership skills relevant to instruction. In addition, we seek candidates with experience in advising undergraduate and masters level students, statistical consulting, and statistical applications.

Applications must be submitted online at (#517862) and must include

(1) a cover letter,

(2) a curriculum vita,

(3) a statement of teaching experience and philosophy,

(4) a statement on contributions to advancing diversity, equity, and inclusion, and

(5) contact information for at least three references.

Review of applications will begin on January 15, 2022, and will continue until the position is filled. The anticipated start date is August 10, 2022, but may be negotiable. Questions regarding the position can be directed by email to Dr. Xinwei Deng, Faculty Search Committee Chair, at .

Open Rank Faculty -Assistant/Associate/Professor

The Virginia Tech Department of Statistics (, in order to support initiatives in data science, data analytics and statistical methodologies,  invites applications for multiple open rank tenured or tenure track faculty positions with focus on environmental and ecological statistics, machine learning, statistical engineering, experimental design, high performance computing, computational statistics, health and applied analytics, uncertainty quantification, or related areas, to begin in Fall 2024.

The position is a 9-month tenure or tenure-track appointment with the opportunity to conduct additional extramurally funded research in the summer. Salary is commensurate with qualifications and experience.

Requirements include a Ph.D. in Statistics, Machine Learning, Biostatistics, Informatics or a closely related field by the time of appointment.

Applications must be submitted online at (#527112) and should include:

  • Cover letter
  • Curriculum vitae
  • Teaching statement
  • Research plan
  • Inclusion statement
  • Contact information for at least three references

Review of applications will begin on October 15, 2023.  As part of the hiring process, the successful applicant must pass a criminal background check. Questions regarding the position can be directed to Professor Robert Gramacy ( chair of this faculty search committee.