Faculty Position in Physical AI and Assured Autonomous Systems

Job Description

The Bradley Department of Electrical and Computer Engineering (ECE)
at Virginia Tech invites applications for a tenure-track or tenured
faculty position at the assistant or associate professor level in
Physical AI and Assured Autonomous Systems. We seek candidates who
develop foundational theory, algorithms, hardware-software systems,
and experimental platforms that enable intelligent physical systems
to perceive, learn, reason, communicate, decide, and act safely,
securely, and reliably in complex, dynamic, and uncertain
environments. Of particular interest are candidates whose work
advances assured autonomy by integrating artificial intelligence
and machine learning with sensing, estimation, control, embedded
and real-time computing, communications, and physical interaction.
The position is based in Blacksburg, Virginia, with opportunities
for collaboration across Virginia Tech's research institutes and
the Institute of Advanced Computing in Alexandria, Virginia. The
successful candidate will be expected to develop and sustain a
nationally recognized, externally funded research program, teach
undergraduate and graduate courses, mentor students, and contribute
to department, college, and university service and outreach
activities.

The ECE department offers B.S., M.Eng., M.S., and Ph.D. degree
programs in both Electrical Engineering and Computer Engineering
with a current enrollment of approximately 1,350 undergraduate and
600 graduate students. The department has 71 full-time tenured or
tenure-track faculty members and 22 non-tenure-track faculty
located in two primary locations, which are the Blacksburg Campus
and the Greater Washington, DC area including the new VT Institute
of Advanced Computing Campus in Alexandria, Virginia. Annual
research expenditures exceed $64M. Recognition of faculty
accomplishments includes 4 members of the National Academy of
Engineering, 32 Fellows of the IEEE, and various fellows of other
professional societies, 27 current and prior NSF CAREER awardees, 1
DARPA Young Faculty Award, and 4 DoD Young Investigators. The
latest Global Universities ranking by U.S. News & World Report
places our department at #5 nationally in the Electrical and
Electronic Engineering category. The department has some of the
nation’s best programs in the areas of fiber optics and photonics,
space science and remote sensing, wireless communications and
networking, power electronics, power systems, autonomous systems,
embedded systems, and computational biology. The Department is the
beneficiary of the Bradley Endowment valued in excess of $20
million. For additional information about the department and the
College of Engineering, please visit www.ece.vt.edu and
www.eng.vt.edu.

We seek outstanding candidates whose research will help establish
Virginia Tech ECE as a leader in the convergence of artificial
intelligence and engineered physical systems. Priority will be
given to work that couples rigorous foundations with deployable,
experimentally validated systems. The search is organized around
three complementary research pillars: (1) Physical AI and embodied
intelligence, including multimodal perception, world models,
learning-enabled control, foundation-model-enabled autonomy,
planning, and intelligent interaction with the physical world; (2)
assured autonomy, including safety, security, robustness,
resilience, formal methods, verification and validation, test and
evaluation, runtime assurance, trustworthy learning and control,
and certifiable autonomous systems; and (3) networked and real-time
autonomous systems, including multi-agent autonomy, cooperative
robotics and swarms, communications-control co-design, edge and
embedded AI, distributed sensing and estimation, human-autonomy
teaming, and experimental cyber-physical platforms. Candidates
whose work bridges these pillars and demonstrates validation
through simulation, digital twins, hardware-in-the-loop,
live-virtual-constructive environments, or field experimentation
are especially encouraged. Application domains may include aerial,
ground, maritime and underwater, space, advanced manufacturing,
transportation, energy and power systems, wireless and networked
systems, critical infrastructure, and other safety- or
mission-critical environments.

This position is intended to strengthen and connect several of
ECE's distinctive capabilities, including autonomous systems and
controls, artificial intelligence and machine learning, embedded
and cyber-physical systems, wireless communications and networking,
cybersecurity, semiconductors and intelligent hardware, sensing,
and power and energy systems. By emphasizing Physical AI, assured
autonomy, and networked/real-time cyber-physical systems, the
position is designed to create a distinctive ECE-centered research
profile that complements rather than duplicates conventional
robotics or computer-science-focused AI programs. The successful
candidate will be expected to build experimental platforms and
collaborative research programs that bridge algorithms, controls,
communications, computing, sensing, and hardware, and that position
Virginia Tech for major federal and industry initiatives in AI for
physical systems, robotics and autonomy, trustworthy and assured
AI, cyber-physical systems, critical infrastructure, advanced
manufacturing, and national security. The candidate will teach
undergraduate and graduate courses in areas such as control
systems, robotics, autonomous systems, artificial intelligence and
machine learning, embedded and cyber-physical systems, real-time
systems, sensing and perception, communications for autonomous
systems, or related topics, as well as specialized graduate courses
in their research area. They will contribute to interdisciplinary
initiatives across Virginia Tech, mentor graduate and undergraduate
researchers, build collaborative research teams, and contribute to
professional and university service activities.

Applicants must apply online at jobs.vt.edu (posting number
538286). Application materials include a cover letter,
curriculum vitae, up to three relevant research publications, and
contact information for at least three references. In addition,
applicants must provide three separate written statements (up to 3
pages each): (1) a research statement; (2) a statement of teaching
and mentoring philosophy; and (3) a statement expressing the
candidate’s ideas for supporting an educational environment
consistent with the Virginia Tech Principles of Community
-specific examples of experiences, activities, and plans will help
us identify candidates who can support and extend our university’s
commitment to inclusive excellence. Review of applications will
commence on Jan 20, 2026, and continue until the position is
filled.

Required Qualifications

An earned Ph.D. in Electrical Engineering, Computer Engineering,
Computer Science, Robotics, Aerospace Engineering, Mechanical
Engineering, or a closely related field, completed prior to
employment.

Demonstrated research and scholarly contributions, or potential for
such contributions, as evidenced by peer-reviewed publications,
conference presentations, research projects, or other relevant
scholarly activities.

Demonstrated ability to develop a research agenda in Physical AI,
assured autonomous systems, controls and learning, networked
autonomy, cyber-physical systems, embedded intelligence, robotics,
or a closely related area, with potential for external funding and
interdisciplinary collaboration.

Demonstrated ability to communicate technical and scientific
information effectively through scholarly publications,
presentations, teaching, or collaborative research
activities.

Demonstrated teaching experience or potential to teach
undergraduate and graduate courses in electrical and computer
engineering or related disciplines, including the ability to use
instructional technologies in educational settings.

Preferred Qualifications

Prior experience as PI or Co-PI on funded research projects, or
strong evidence of potential to establish an externally funded
research program.

Ability and willingness to collaborate with faculty from a variety
of disciplines and to build multi-investigator research
teams.

Experience working with or mentoring undergraduate and graduate
students in research.

Interest or experience working effectively with a diverse student
population.

Demonstrated theoretical, computational, or experimental expertise
in one or more of the following three areas is highly desirable:
Physical AI and embodied intelligence: multimodal perception, world
models, foundation-model-enabled autonomy, learning for control and
planning, sensorimotor intelligence, and intelligent interaction
with the physical world; Assured autonomy: safe and trustworthy
learning and control, formal methods, verification and validation,
test and evaluation, runtime assurance, robustness, resilience,
security, uncertainty-aware decision-making, and certifiable
autonomous systems; Networked and real-time autonomous systems:
robotics, multi-agent and cooperative autonomy,
communications-control co-design, human-autonomy teaming,
edge/real-time AI, distributed sensing and estimation, embedded
intelligence, and experimental cyber-physical platforms

Candidates should also demonstrate the ability and enthusiasm to
teach foundational ECE courses in areas such as controls, embedded
systems, robotics, artificial intelligence/machine learning,
cyber-physical systems, communications/networking, or computer
engineering, as well as advanced electives in Physical AI and
autonomous systems.

Particularly strong candidates will show the ability to connect
foundational research with experimental platforms, large
collaborative programs, and application domains aligned with ECE
and Virginia Tech strengths.

Overtime Status

Exempt: Not eligible for overtime

Appointment Type

Regular

Salary Information

$120,000–$150,000

Hours per week

40

Review Date

Jan 20, 2027, and continue until the position is 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 Cole Tankersley at cpt19@vt.edu during regular business
hours at least 10 business days prior to the event.