Opportunities

Prospective PhD Students

We are recruiting multiple PhD students to join our research group starting Fall 2026 or Spring 2027. Our work explores hardware-software co-design for energy-efficient, intelligent computing systems that will power next-generation AI, with a focus on two complementary directions:

• Brain-inspired circuits and architectures based on CMOS and emerging memory devices
• Energy-efficient algorithms and applications with analog in-memory computing hardware

Why Join Our Team?

Collaborative mentorship and research development

Our group emphasizes hands-on mentorship combined with the freedom to pursue ambitious research directions. Team members benefit from collective experience spanning both hardware and software, with a track record of publishing in leading engineering venues (e.g., IEEE Transactions) as well as high-impact interdisciplinary journals (e.g., Nature series). Feel free to reach out to collaborators to hear about their experience working with us.

Interdisciplinary and collaborative environment

Our EECS department houses programs in Electrical Engineering, Computer Engineering, and Computer Science, creating collaboration opportunities across the full hardware-to-software stack. The department is also home to a leading research team (TENN Lab) in neuromorphic architectures, learning, and applications, a natural foundation for interdisciplinary work. In addition, proximity to Oak Ridge National Laboratory offers opportunities to collaborate with a world-class research facility.

Life beyond the lab

Research is a marathon, not a sprint, and we value a balanced style. Great Smoky Mountains National Park is right around the corner for our group hiking, camping, and outdoor adventures. Fitness and wellness are also part of our group culture, with guidance available from the PI, an ACE-certified personal trainer and nutrition specialist.

Who We’re Looking For:

We are seeking self-motivated students who love exploring what’s next. Ideal candidates have:

• An interest in brain-inspired circuits, architectures, and algorithms for next-generation AI
• A strong background in analog circuit design or machine learning algorithms
• Previous experience with neuromorphic computing or in-memory computing is a plus

How to Apply:

Students interested in joining the team are encouraged to email yihuang@utk.edu with: 1) your CV, 2) your transcripts, 3) a brief statement of your research interests and career goals, and 4) your TOEFL or IELTS score (if applicable).