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 focusing on Physical Artificial Intelligence (AI). The position is based in Blacksburg, Virginia, with opportunities for collaboration across Virginia Tech’s Institute of Advanced Computing (Alexandria, VA) and other university research institutes. The successful candidate will be expected to develop and maintain a nationally recognized funded research program, teach undergraduate and graduate courses, and participate in 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 1,300 undergraduate and 670 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 $56M. Recognition of faculty accomplishments includes 4 members of the National Academy of Engineering, 30 Fellows of the IEEE, and various fellows of other professional societies, 27 current and prior NSF CAREER awardees, and 4 DoD Young Investigators. The latest Global Universities ranking by U.S. News & World Report (USN&WR) places our department at #3 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 a visionary scholar to pioneer the convergence of AI with physical laws, materials, devices, and engineered systems, enabling predictive, trustworthy, and autonomous operation of complex physical platforms. The successful candidate will develop AI-native models, digital twins, and control frameworks that bridge the loop between theory, simulation, experimentation, and deployment across one or more of ECE’s core strength areas, including:
• Semiconductors and micro/nanofabrication
• Photonics and optoelectronics
• Quantum and cryogenic devices
• Wireless, communications, networking, and sensing systems
• Power electronics, power systems, and energy infrastructure
This position aligns with national priorities in AI-for-Science, the Genesis Mission, CHIPS and Science Act initiatives, autonomous laboratories, resilient cyber-physical systems, and next-generation infrastructure, and complements Virginia Tech’s strong interdisciplinary ecosystem spanning ECE, computing, materials, and applied sciences.
Research Focus
We invite candidates whose research advances Physical AI—AI systems that reason over, learn from, and act within the physical world, grounded in first principles and experimental reality. Areas of interest include, but are not limited to:
• Physics-Informed and Hybrid AI Methods: Physics-Informed Neural Networks (PINNs), operator learning, and neural surrogates; hybrid modeling combining governing equations, simulations, and data; uncertainty-aware learning, interpretability, and robustness for physical systems; and inverse problems, co-design, and constrained learning under physical laws.
• Digital Twins and Autonomous Physical Systems: Multi-scale digital twins linking devices, processes, and systems; AI-enabled Design–Build–Test–Learn (DBTL) acceleration; autonomous experimentation, adaptive control, and self-driving laboratories; and secure, reproducible, and standards-aligned twin infrastructures.
Candidates may focus on one or more domains such as: Semiconductor devices and nanomanufacturing (process control, yield learning, variability, reliability); Photonics and optoelectronics (inverse design, fabrication-aware modeling, nonlinear or multi-physics systems); Quantum and cryogenic platforms (noise modeling, calibration, control, materials–device coupling); Wireless and sensing systems (AI-native PHY/MAC, RF-aware learning, joint sensing–communications); Power electronics and power systems (physics-aware grid modeling, stability, protection, resilience, microgrids); Cross-domain work that transfers Physical AI methods across platforms.
This position offers an opportunity to shape the future of computing at Virginia Tech through research, teaching, and service. The candidate will teach core courses in computer engineering—such as embedded systems, computer architecture, and network application design—as well as specialized graduate courses in their research area. They will contribute to interdisciplinary initiatives with the Institute of Advanced Computing (IAC), the Commonwealth Cyber Initiative (CCI), the National Security Institute (NSI), the Institute for Creativity, Arts, and Technology (ICAT), and the Institute for Critical Technology and Applied Science (ICTAS). In addition, they will mentor graduate students and postdoctoral researchers and contribute to professional and university service activities.
This position offers an opportunity to contribute to interdisciplinary initiatives with the Institute of Advanced Computing (IAC), the Commonwealth Cyber Initiative (CCI), the National Security Institute (NSI), the Institute for Creativity, Arts, and Technology (ICAT), and the Institute for Critical Technology and Applied Science (ICTAS). In addition, they will mentor graduate students and postdoctoral researchers and contribute to professional and university service activities.
Applicants must apply online at jobs.vt.edu. 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 3/15/2026, and continue until the position is filled.
