PhD and Postdoc Positions in Wireless, Optical, Quantum Networks and Energy-Efficient Computing at Duke University
The FuNCtions Lab at Duke University, led by Assistant Professor Tingjun Chen, is recruiting several PhD students and postdoctoral researchers for Fall 2026. The lab focuses on cutting-edge research in networking, communication, sensing, and energy-efficient computing, spanning wireless, mobile, optical, and quantum networked systems. Projects cover both theoretical and experimental domains, utilizing SDR and RFSoC/FPGA platforms, commercial-grade telecom systems, large-scale measurements, and digital twins, all enhanced with machine intelligence and AI/ML techniques.
Successful candidates will have opportunities to collaborate within the SRC/DARPA JUMP 2.0 Center for Ubiquitous Connectivity (CUbiC), the NSF Athena AI Institute, and other interdisciplinary research initiatives. The lab's research interests include massive antenna systems, millimeter-wave networks, optical and quantum networks, spectrum sharing, edge cloud convergence, and intelligent IoT systems. Ongoing projects are supported by grants from NSF, ARO, SRC/DARPA, and industry partners such as Google, IBM, NEC Labs America, NTT, and NVIDIA.
Applicants should be motivated and creative, with backgrounds in electrical engineering, computer science, or related fields. Experience with hardware-software systems, experimental testbeds, and machine intelligence is highly valued. PhD candidates typically require a bachelor's or master's degree in a relevant discipline, while postdoc applicants should hold a PhD. The positions are likely fully funded, with support from major research grants and initiatives, though specific financial details are not provided.
To apply, candidates should email their CV, transcript, and a brief note about their research interests to Prof. Tingjun Chen. For more information, visit the lab website or reach out directly. The application deadline is December 28, 2025.
Keywords: wireless networks, mobile networks, optical networks, quantum networks, energy-efficient computing, networking, communication, sensing, machine intelligence, SDR, RFSoC, FPGA, telecom systems, digital twins, AI/ML, edge computing, IoT.
