Mathematics, Virginia Tech

Position ID: VirginiaTech-CMDAPOP [#13249, TR0180182]
Position Title: CMDA Professor of Practice
Position Type: Non tenure-track faculty
Position Location: Blacksburg, Virginia 24061, United States [map]
Subject Area: Division of Computational Modeling and Data Analytics (CMDA)
Application Deadline: 2019/01/22 (posted 2018/11/26, listed until 2019/02/28)
Position Description:    

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) to begin on June 25, 2019. Requirements for this 12-month position include: a master’s degree in Computer Science, Mathematics, Statistics or a closely related field, and significant experience in the practice of computational science or data analytics in industrial or laboratory settings.

The successful applicant will lead the CMDA major’s Capstone Project program and industrial engagement efforts. The Capstone Project course sets small teams of CMDA seniors to work on nontrivial, open-ended modeling problems that are proposed by clients from industry and academia. (See www.math.vt.edu/people/embree/cmda4864 for details about the Fall 2018 Capstone class.) Expectations for this Professor of Practice include: effective engagement with industry partners to solicit capstone projects and identify additional student opportunities, such as internships; thoughtful mentorship of students as they tackle diverse, open-ended projects; management of the Capstone course team and teaching assistants; development of a systematic industrial relations program for CMDA; 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 http://www.provost.vt.edu) provides a complete description of faculty responsibilities. Required qualifications Applicants must have a strong background in computational science or data analytics, with demonstrated experience solving interdisciplinary problems in an industrial or laboratory setting; the ability to teach students with diverse interests, backgrounds, and abilities as they tackle open-ended, ambiguous problems; 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. Preferred qualifications Preference will be given to candidates with: several years of experience collaborating on analytic problems within industry, government, or academia; experience teaching practical problem-solving skills to students and/or colleagues; experience teaching professional skills (e.g., teamwork, leadership, project management, technical writing, oral and visual communications) to students and/or colleagues; experience engaging with clients from a variety of industries, organizations, and/or disciplines. How to apply Questions regarding the position can be directed to Professor Mark Embree (embree@vt.edu), chair of the search committee. Review of applications will begin on January 22, 2019. As part of the hiring process, the successful applicant must pass a criminal background check.

Applications must be submitted online https://listings.jobs.vt.edu/postings/92120 and should include a cover letter; curriculum vitae; and a teaching statement that describes the candidate’s experience leading or mentoring interdisciplinary computational science/data analytics team projects. Applications must also include contact information for at least three references.

Virginia Tech is an EO/AA university, and offers a wide range of networking and development opportunities to women and minorities in science and engineering. Virginia Tech is committed to a culturally and ethnically diverse campus environment and to principles that promote inclusive practices. More information is available at http://www.inclusive.vt.edu/index.html. The Academy of Integrated Science offers a supportive environment for faculty. Individuals with disabilities desiring accommodations in the application process should notify Dr. Nora Dragovic, Academy of Integrated Science, Tel: (540) 231-8131, Email: nora84@vt.edu.


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Contact: Mark Embree
Email:
Postal Mail:
Search Committee
Mathematics Department
Virginia Tech
Blacksburg, VA 24061
Web Page: https://www.math.vt.edu

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