About the Position:
- We are seeking a highly motivated PhD candidate to join our research group working on next-generation neuromorphic computing systems. This project focuses on designing secure and energy-efficient architectures inspired by the human brain, enabling intelligent processing at the edge with minimal power consumption. The successful candidate will contribute to cutting-edge research at the intersection of hardware design, artificial intelligence, and cybersecurity, addressing key challenges in scalable, trustworthy neuromorphic systems.
Research Objectives:
- Design and evaluate low-power neuromorphic hardware architectures
- Develop security mechanisms for neuromorphic and AI accelerators (e.g., side-channel resistance, secure learning)
- Explore emerging technologies (e.g., memristors, in-memory computing, event-driven systems)
- Implement and benchmark architectures using simulation frameworks and/or hardware prototypes
- Collaborate with interdisciplinary teams in AI, circuits, and embedded systems
Candidate Profile:
- Master’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field
- Strong background in the following areas:
- Digital/analog IC design
- Computer architecture
- Machine learning or neuromorphic computing
- Experience with hardware description languages (e.g., Verilog, VHDL) or system-level modeling (e.g., SystemC, Python)
- Knowledge of hardware security is a plus
- Strong analytical skills and ability to work independently and collaboratively
- Proficiency in English (written and spoken)
