Faculty Position in Physical AI and Assured Autonomous Systems

About the role

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. 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 ECE department offers B.S., M.Eng., M.S., and Ph.D. degree programs in both Electrical Engineering and Computer Engineering with approximately 1,350 undergraduate and 600 graduate students. The department has 71 full-time tenured or tenure-track faculty and 22 non-tenure-track faculty across the Blacksburg campus and the Greater Washington, DC area including the VT Institute of Advanced Computing campus in Alexandria. Annual research expenditures exceed $64M. Faculty recognition includes 4 National Academy of Engineering members, 32 IEEE Fellows, 27 NSF CAREER awardees, and the department is ranked #5 nationally in Electrical and Electronic Engineering by U.S. News & World Report. The department is the beneficiary of the Bradley Endowment valued in excess of $20 million.

Research focus

The search is organized around three complementary research pillars. 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.

• Physical AI and embodied intelligence: multimodal perception, world models, learning-enabled control, foundation-model-enabled autonomy, planning, and intelligent interaction with the physical world
• Assured autonomy: safety, security, robustness, resilience, formal methods, verification and validation, test and evaluation, runtime assurance, trustworthy learning and control, and certifiable autonomous systems
• Networked and real-time autonomous systems: 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

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. The position is designed to strengthen and connect ECE's distinctive capabilities in autonomous systems and controls, AI and machine learning, embedded and cyber-physical systems, wireless communications and networking, cybersecurity, semiconductors and intelligent hardware, sensing, and power and energy systems.

Responsibilities

• Develop and sustain a nationally recognized, externally funded research program
• 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 the candidate's research area
• Mentor graduate and undergraduate researchers
• Build collaborative research teams and experimental platforms that bridge algorithms, controls, communications, computing, sensing, and hardware
• Contribute to department, college, and university service and outreach activities
• Contribute to interdisciplinary initiatives across Virginia Tech
• Participate in professional and university service activities

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 three research pillars (Physical AI and embodied intelligence, assured autonomy, networked and real-time autonomous systems)
• Ability and enthusiasm to teach foundational ECE courses in controls, embedded systems, robotics, AI/ML, cyber-physical systems, communications/networking, or computer engineering, as well as advanced electives in Physical AI and autonomous systems
• Ability to connect foundational research with experimental platforms, large collaborative programs, and application domains aligned with ECE and Virginia Tech strengths

Compensation and schedule

Salary range: $120,000–$150,000. This is a regular, exempt (not eligible for overtime) appointment at 40 hours per week.

Review timeline

Review of applications will commence on January 20, 2027, and continue until the position is filled.

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