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.