ECE Tenure-Track Faculty Position in Physical AI

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 focusing on Physical Artificial Intelligence (AI). The position is based in Blacksburg Virginia with opportunities for collaboration across Virginia Techs 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.S. and Ph.D. degree programs in both Electrical Engineering and Computer Engineering with a current enrollment of approximately 1300 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 nations 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 and .

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 ECEs 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 Techs strong interdisciplinary ecosystem spanning ECE computing materials and applied sciences.
Research Focus
We invite candidates whose research advances Physical AIAI 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 DesignBuildTestLearn (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 materialsdevice coupling); Wireless and sensing systems (AI-native PHY/MAC RF-aware learning joint sensingcommunications); 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 engineeringsuch as embedded systems computer architecture and network application designas 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 . Application materials include a cover letter curriculum vitae up to three relevant research publications and contact information for at least three 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 candidates ideas for supporting an educational environment consistent with the Virginia Tech Principles of Communityspecific examples of experiences activities and plans will help us identify candidates who can support and extend our universitys commitment to inclusive excellence. Review of applications will commence on 3/15/2026 and continue until the position is filled.

Required Qualifications

Ph.D. (by start date) in Electrical and Computer Engineering or a closely related field.
Demonstrated research potential or accomplishments in Physical AI Physics-Informed AI or AI for physical systems.
Strong grounding in physical modeling devices systems or experimentation relevant to ECE.
Evidence of potential to secure competitive extramural funding.
Commitment to excellence in teaching mentoring and inclusive academic practices.

Preferred Qualifications

Experience with experimental platforms fabrication hardware systems or large-scale physical infrastructure.
Experience with multi-physics modeling simulation or scientific computing.
Experience bridging theory computation and real-world data.
Experience with secure data workflows reproducibility or shared research infrastructure.
Demonstrated interest in interdisciplinary or cross-domain Physical AI

Overtime Status

Exempt: Not eligible for overtime

Appointment Type

Regular

Hours per week

40

Review Date

March 15 2026 and remain open until filled

Additional Information

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

About Virginia Tech

Dedicated to its mottoUt 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 aninclusive communitydedicated to knowledge discovery and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36000 undergraduate graduate and professional students in eightundergraduate colleges aschool of medicine aveterinary medicinecollegeGraduate School andHonors 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 numerousExtension officesandresearch 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.