Assistant Professor

Virginia AG; Blacksburg (VA); On-site; USD 120,000 - 170,000; Full time

Job summary

Virginia Tech invites applications for a tenure-track Assistant Professor position in the Department of Economics, starting August 2027. The candidate should establish an internationally recognized research program in Economics, Data Science, or related areas, with a focus on data, computation, and quantitative methods to address economic and societal questions.

The role includes developing research, teaching undergraduate and graduate courses, and engaging in interdisciplinary activities across

Qualifications

• Earned Ph.D. by appointment date in Economics, Data Science, or related field.
• Strong potential for internationally recognized research in data-intensive inquiry.
• Ability to teach undergraduate and graduate levels and mentor students in data-driven methods.

Responsibilities

• Develop and maintain a high-quality research program.
• Teach at undergraduate and graduate levels.
• Engage in interdisciplinary collaboration across the university.

Skills

Interdisciplinary collaboration

Communication skills

Teaching experience

Education

Ph.D. in Economics/Data Science or related field

Job description

Job Description

The Department of Economics at Virginia Tech invites applications for a tenure-track Assistant Professor position beginning August 2027. We seek candidates with the potential to establish an internationally recognized research program in Economics, Data Science, or related disciplines, with interests broadly connected to the use of data, computation, and quantitative methods to address important economic, business, technological, or societal questions. We particularly value candidates whose research incorporates emerging technologies, including artificial intelligence (AI), machine learning, or related innovations, or who employ modern computational and data-intensive methods to address economic questions and inform decision-making. The successful candidate will be expected to contribute to the department’s research mission, teach at the undergraduate and graduate levels, and participate in interdisciplinary activities across the university.

The successful candidate will be expected to develop and maintain a high-quality research program, contribute to undergraduate and graduate teaching, and participate in the intellectual life of the department and university. Candidates should demonstrate the potential to produce impactful scholarship, engage in interdisciplinary collaboration, and contribute to the training of students in data-driven methods and applications. Salary and teaching assignments will be commensurate with qualifications and experience.

Required Qualifications

Applicants must have earned a Ph.D. by the date of appointment in Economics, Data Science, or a closely related field.

Candidates should demonstrate strong potential for developing an internationally recognized research program in areas related to data-intensive inquiry, including but not limited to artificial intelligence, machine learning, big data analytics, computational social science, network science, or other domains involving the analysis and use of large-scale data.

Successful applicants must show evidence of the ability to teach effectively at the undergraduate and graduate levels and to mentor students in data-driven methods and applications.

Candidates should possess excellent written, oral, and interpersonal communication skills, as well as a demonstrated interest in interdisciplinary research and collaboration across fields.

The successful candidate will be expected to contribute to a vibrant research and teaching environment through high-quality scholarship, innovative instruction, and engagement with colleagues across the university.

Preferred Qualifications

Preference will be given to candidates whose research addresses important economic, business, technological, societal, or policy challenges through the analysis and use of large-scale data.

Demonstrated interest in interdisciplinary collaboration across fields such as Economics, Data Science, Computer Science, Statistics, Engineering, and Business is desirable. Experience developing innovative courses or training opportunities in machine learning, artificial intelligence, data science, or analytics is an asset.

Candidates whose scholarship combines methodological innovation with substantive applications, and who show strong potential for developing externally funded collaborative research programs, are especially encouraged to apply.

Overtime Status

Exempt: Not eligible for overtime

Appointment Type

Regular

Salary Information

Commensurate with experience

Hours per week

40 hours - exempt position

Review Date

December 12, 2026

Additional Information

A completed application must include a cover letter, curriculum vitae, research statement, teaching statement, and the names and contact information of three references.

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

Some travel to meetings and conferences may be required.

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 inclusive community 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 undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College.The university has a significant presence across Virginia, including Blacksburg, the greater Washington, D.C. area, the Health Sciences and Technology Campus in Roanoke, sites in Newport News and Richmond, and numerous Extension offices and research institutes. A leading global research institution, Virginia Tech conducts more than $650 million in research annually.

Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance. These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development.

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, ethnicity or 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 Lynn Gentryat [e-mail] during regular business hours at least 10 business days prior to the event.