The Virginia Tech Academy of Integrated Science (www.ais.science.vt.edu) invites applications for a Professor of Practice faculty position in the Division of Computational Modeling and Data Analytics (CMDA) (www.ais.science.vt.edu/academics/cmda.html) to begin on August 10, 2021. Requirements for this 12-month position include: a master’s degree or doctorate in Computer Science, Mathematics, Statistics or a closely related field, and a demonstrated record of achievement in the practice of computational science or data analytics in business, government, nonprofit, and/or research settings.The successful applicant will join the CMDA major’s Capstone Project team and support organizational engagement activities for CMDA. The Capstone Project course sets small teams of CMDA seniors to work on nontrivial, open-ended modeling problems that are proposed by clients from business, government, and academia. Expectations for this Professor of Practice include: effective engagement with outside partners to solicit Capstone projects and identify additional student opportunities, such as internships; thoughtful mentorship of students as they tackle diverse, open-ended projects and develop professional skills; help with management of the Capstone course and teaching assistants; cultivation of long term relationships with partners at Virginia Tech as well as in business, government, nonprofits, and outside academic institutions; and participation in service activities within the CMDA division. CMDA is an interdisciplinary program involving collaboration from several departments. The successful applicant will join the faculty in the Department of Mathematics, the Department of Statistics, or the Academy of Integrated Science, depending on background. The faculty handbook (available at www.provost.vt.edu/) provides a complete description of faculty responsibilities.
Applicants must have a strong background in computational science or data analytics, with demonstrated leadership solving interdisciplinary problems in a business, government, or research setting; the ability to teach students with diverse interests, backgrounds, and abilities as they tackle open-ended, ambiguous problems; and commitment/sensitivity to address issues of diversity in the university community. Applicants must have earned a master’s degree or doctorate in Computer Science, Mathematics, Statistics, or a related field at the time of appointment.