Professor of Practice

3 weeks ago

Blacksburg, United States Commonwealth of Virginia Full time

Job Description

The Virginia Tech Academy of Data Science (ADS) () invites applications for multiple Professor of Practice faculty positions at the rank of assistant, associate or full professor, depending on credentials and experience, to begin during the Fall 2024 semester (classes begin August 26, specific starting date negotiable).

Requirements for these full-time, 12-month positions include: a doctoral or master’s degree in Statistics, Data Science, Computer Science, Mathematics, or other closely related field; a demonstrated and sustained record of achievement in the practice of data analytics or computational science in business, government, nonprofit, academic and/or research settings; and experience in leadership or management roles in such settings. Additionally, candidates should have a demonstrated record of instruction and communication in the relevant fields. Experience teaching advanced concepts in undergraduate, graduate, and/or professional courses will be favorably considered.

The successful candidate will play a central role in the development and delivery of the Academy’s degree programs: the expected Master of Science in Data Science (MS) and the current undergraduate (BS) degree in Computational Modeling and Data Analysis (CMDA).

Responsibilities include:

• Developing overall programmatic content and concentrations for the Academy’s degree programs informed by experience in the settings described above and in consultation with organizational leaders.

• Developing new courses in data analytics, data-driven applications, industrial applications, and communications in technical settings.

• Teaching courses in either of the degree programs depending on demand as determined by the Director of the Academy.

• Workload consisting of 90% teaching and/or research and 10% service.

• Effective engagement with external organizations in the private sector and with government agencies resulting in the definition and execution of student capstone projects for the MS and CMDA programs.

• Mentoring students in support of their capstone project activities in the MS and CMDA programs.

• Developing and nurturing relationships outside of academia that can result in internship and job placement activities for our students and partnership opportunities for the Academy as a whole.

• Advising and mentoring students in the Academy’s degree programs.

• Supporting other faculty who are seeking external funding opportunities that align with the objective of establishing Virginia Tech as a leader and innovator in the application of Data Science in support of scientific research and other application areas.

• Cooperating with the College of Science Advancement team in fostering external relationships that promote philanthropic support of the College and identify opportunities for new partnerships with the Academy.

• Maintaining knowledge of other programs and future industry needs to advise the Academy of Data Science Director and College of Science Dean on new opportunities and directions that ensure that the Virginia Tech programs are innovative and of high value.

Required Qualifications

Applicants must have a strong background in data analytical/mathematical/statistical methods and/or computational science.

The successful candidate will have demonstrated a sustained record of achievement solving interdisciplinary problems in a business, government, or academic setting.

Leadership experience in this context is required.

Excellent communication skills with the ability to build, nurture and maintain relationships with external stakeholders is essential.

A commitment to equity, inclusion and diversity is required.

Applicants must possess a PhD or Masters level degree in statistics, computer science, applied mathematics or a related field as applied to data science.

Preferred Qualifications

Preference will be given to candidates who possess substantial experience in business and/or government.

Experience working in or with a variety of industries, organizations, and/or disciplines is strongly desired.

Experience teaching graduate, undergraduate, and/or professional students, and mentoring student projects or research experiences, will receive favorable consideration.

It is also preferred that candidates have a doctorate degree in data science, statistics, computer science, applied mathematics or related fields as applied to data science.

Appointment Type

Regular

Salary Information

Commensurate with experience

Review Date

August 1, 2024; open until filled

Additional Information

A complete application will include a current CV, a one page cover letter that outlines your experience and interest in the position, and a list of three professional references with their preferred contact information. Additionally, please provide a one page statement that includes an overview of your commitment to diversity, equity and inclusion.

The successful candidate will be required to have a criminal conviction check.

About Virginia Tech

Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight , a , a college, , and . The university has a significant presence across Virginia, including the in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous and . A leading global research institution, Virginia Tech conducts more than $500 million in research annually.

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.

If you are an individual with a disability and desire an accommodation, please contact Cherie Nelson at during regular business hours at least 10 business days prior to the event.

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