Assistant/Associate/Full Professor in intelligent mining systems and automation

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.