The research group of Dr. Suya in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville (UTK) is seeking a Postdoctoral Research Associate to contribute to externally funded research in trustworthy AI, adversarial machine learning, and the security of physical/cyber-physical AI systems. The position is for one year in the first instance, with the possibility of extension contingent on performance and funding. The successful candidate will lead and contribute to research projects at the intersection of trustworthy AI, security and privacy of cyber-physical and IoT systems, and physical-layer adversarial attacks against AI-enabled sensing and recognition systems. The position offers significant autonomy in shaping research directions, opportunities to co-author publications at top venues (CCS, NDSS, USENIX Security, IEEE S&P), mentor graduate/undergraduate students, and participate in proposal development for federal funding agencies (NSF, DARPA, ARO, DoE).

• Lead and participate in research projects in one or more of the following areas: trustworthy AI; security and privacy of cyber-physical and IoT systems; side-channel attacks and defenses on AI workloads; or physical-layer attacks against AI-enabled sensing and recognition.

• Co-advise and mentor graduate and undergraduate student researchers on related projects.

• Co-author publications at top venues (e.g., CCS, NDSS, USENIX Security, IEEE S&P).

• Contribute to proposal development for federal funding agencies (e.g., NSF, DARPA, ARO, DoE).

Required Qualifications

• Education: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a closely related field (completed by start date).

• Experience: Demonstrated record of peer-reviewed publications in security, machine learning, or cyber-physical systems.

• Knowledge, Skills, Abilities: Strong programming skills (Python and/or C/C++) and experience with ML frameworks (PyTorch or TensorFlow); excellent written and verbal communication skills in English.

Preferred Qualifications

• Education: Ph.D. with a dissertation focus in security, machine learning, cyber-physical systems, or a closely related area.

• Experience: First-author publications at top-tier security venues (e.g., CCS, NDSS, USENIX Security, IEEE S&P); experience mentoring graduate or undergraduate researchers; service to the research community (paper reviewing, workshop organization).

• Knowledge, Skills, Abilities: Expertise in one or more of: adversarial ML, side/covert channels, sensor-driven attacks, IoT/CPS security; background spanning both systems-level (embedded systems, signal processing, wireless/communications) and AI/ML research is a plus.

Work Location

• Location: Knoxville, Tennessee

• Onsite

Compensation and Benefits

• Anticipated hiring range: Competitive, commensurate with experience. UTK provides comprehensive benefits including health insurance, retirement contributions, and paid time off.

• Find more information on UT Benefits here

Application Instructions

For full consideration, please submit an application with the noted below attachments:

• Curriculum Vitae (with full publication list)

• Cover letter describing research interests, relevant experience, and career goals

• Research statement (1–2 pages) on past work and proposed directions

All related inquiries should be directed to Fnu Suya at fsuya@utk.edu.

About The Department

The University of Tennessee, Knoxville (UTK) is an R1 research university located in Knoxville, Tennessee, with strong collaborative ties to Oak Ridge National Laboratory (ORNL) — one of the largest U.S. Department of Energy national laboratories — offering unique opportunities for joint research in AI security, cyber-physical systems, and high-performance computing.

The Min H. Kao Department of Electrical Engineering and Computer Science houses internationally recognized faculty and research programs spanning AI/ML, security, embedded and cyber-physical systems, computer architecture, and data science. Knoxville offers a low cost of living and quick access to the Great Smoky Mountains and Oak Ridge National Laboratory.