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# Faculty Position in Physical AI and Assured Autonomous Systems

- **Company:** Virginia Polytechnic Institute And State University
- **Location:** Blacksburg, VA, United States
- **Salary:** $120,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Engineering, Machine Learning, Cyber-physical Systems, Verification and Validation (Software), Electrical and Computer Engineering, Multi-Agent Systems, Formal Methods
- **Published:** October 18, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=22e6a846be647d65

## About the Role

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.