The SeDIS Lab at the University of Texas at Dallas is inviting applications for fully funded Ph.D. positions starting in Fall 2026. The lab specializes in intelligent edge systems that operate reliably under real-world uncertainty and resource constraints, with research spanning sensing operations, efficient on-device computing, and system-level decision-making. The group conducts research in system-level intelligence for autonomy, learning for reliable on-device intelligence, and AI hardware for compute-efficient edge intelligence. Key areas include mission-driven decision-making, trust-aware coordination, real-time planning for autonomous systems, lightweight and uncertainty-aware learning methods, and energy-efficient AI hardware such as compute-in-memory and mixed-signal accelerators.

Applicants should hold a B.S. or M.S. in Electrical and Computer Engineering or a closely related field, possess strong programming skills in Python (for machine learning) or C++ (for embedded systems), and demonstrate clear technical communication in English. Motivation for cross-disciplinary research connecting sensing, computing, and learning is essential. Candidates with prior research or industry experience in machine learning, deep learning, VLSI, analog or mixed-signal circuits for edge computing are strongly encouraged to apply, especially if they can demonstrate experience through publications, projects, or professional work.

Funding for these positions is fully provided, including tuition coverage and a stipend. The application process involves contacting Dr. Minah Lee for research fit questions (optional), emailing preliminary materials (Statement of Purpose, CV, unofficial transcripts, and optional publications or GitHub links), and submitting a formal Ph.D. application to UT Dallas with a clear indication of interest in the SeDIS Lab. Shortlisted candidates will be invited for interviews in January. The deadline for applications is December 28, 2025.

Research keywords include edge intelligence, machine learning, deep learning, system-level autonomy, on-device computing, AI hardware, mixed-signal circuits, VLSI, electrical engineering, and computer engineering. The SeDIS Lab offers a dynamic environment for students interested in advancing the state-of-the-art in intelligent systems and hardware for edge computing.