Job Description

The Department of Mining and Minerals Engineering at Virginia Tech invites applications for an open rank tenured or tenure-track faculty position in intelligent mining systems and automation. Areas of specific interest include, but are not limited to: mine systems, optimization and digitization; autonomous mining; robotics and intelligent machines; artificial intelligence and machine learning for mining applications; digital twins; human-machine interaction; analytics and real-time decision-making. We seek an innovative and collaborative scholar who will contribute to the department’s collegial, interdisciplinary environment and strengthen its longstanding excellence in fundamental and applied research, education, and engagement with the mining industry. Highly qualified and distinguished applicants may be eligible for a named professorship that will provide salary and operational support.

The Virginia Tech Department of Mining and Minerals Engineering has long-established excellence in the field, including two current and former National Academy of Engineering members and several top ranked global scholars. The recently renovated Holden Hall, the long-term home of the department, provides state-of-the-art facilities for department personnel, including the Autonomous Mining Arena. The department also enjoys close partnership with industry, and currently convenes the Built for the Mine partnership, an education and research-oriented collective that includes 12 leading mining technology companies and producers. The department currently has nearly 20 tenure-line, instructional, and research faculty members and is home to over 120 undergraduate and graduate students. The department’s teaching, research, and operations are centered around core values that include Technical Excellence, Leadership, Community, and Resilient Creativity.

The successful candidate will have a PhD in Mining Engineering or a closely related field at time of appointment, a strong record of academic accomplishments and a proven ability to work collaboratively, a commitment to interdisciplinary research and instruction, and a willingness to expand disciplinary boundaries to address complex technical and societal challenges. The successful candidate will have a high potential to build an independent, coherent, and robust area of scholarship; the ability to effectively advise PhD students, the ability to teach required undergraduate courses in our curriculum, and identify needs for and develop new courses.

Applicants must apply online at jobs.vt.edu. Application materials include a cover letter, CV, up to three relevant research publications, and contact information for at least three professional references. In addition, applicants must provide a research statement and a statement of teaching and mentoring philosophy (up to 3 pages each). Review of applications will commence on November 1, 2026 and continue until the position is filled. Questions regarding the position should be directed to Nino Ripepi (nripepi@vt.edu).

Required Qualifications

At the time of appointment, the successful candidate will have:

• A PhD in mining engineering or a closely related field. Candidates with degrees outside mining engineering must demonstrate scholarly, industrial, or other experience relevant to mining or mineral systems;
• Demonstrated expertise in intelligent mining systems and automation, including one or more areas such as mine systems, optimization and digitization; autonomous mining; robotics and intelligent machines; artificial intelligence and machine learning for mining applications; digital twins; human-machine interaction; data analytics and real-time decision-making; or closely related areas;
• A record of scholarly accomplishment, or demonstrated potential for scholarly impact, commensurate with the candidate's career stage and proposed rank;
• The potential to establish and sustain an independent, externally supported research program that advances fundamental or applied scholarship relevant to mining and mineral systems;
• The demonstrated ability to contribute effectively to interdisciplinary and collaborative research, including work that connects mining engineering with complementary technical disciplines;
• A proven ability to work collaboratively, contributing to or leading interdisciplinary team commensurate with rank;
• The work history showing the ability and interest to teach and mentor students effectively at the undergraduate and graduate levels, including contributing to core mining engineering instruction and developing curricular offerings related to the candidate's area of expertise

Preferred Qualifications

Preferred Qualifications

• A record of externally funded research, scholarly impact, and graduate student mentorship commensurate with career stage and proposed rank;
• Experience developing or leading collaborative research involving multiple investigators, disciplines, institutions, or industry partners;
• Experience collaborating across technical disciplines such as computer science, mechanical engineering, robotics and autonomous systems, mechatronics, electrical and computer engineering, safety engineering or related fields; and
• Industrial experience or sustained engagement with the mining, minerals, automation, or related technology sectors.

Overtime Status

Exempt: Not eligible for overtime

Appointment Type

Regular

Salary Information

$110,000 - $170,000 or commensurate with experience

Hours per week

40

Review Date

11/1/2026 until filled

Additional Information

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 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 Annie Lawrence at annie.lawrence@vt.edu during regular business hours at least 10 business days prior to the event.