PhD position in Neuromorphic Computing, FPGA Design, and Hardware Acceleration

Official university vacancy imported from University of Groningen. Details are presented for discovery and may change. Confirm the latest requirements and apply on the official source.

Are you excited about designing the next generation of energy-efficient AI hardware? Do you want to contribute to cutting-edge research at the intersection of neuromorphic computing, computer architecture, and hardware acceleration?

The University of Groningen is seeking a highly motivated PhD candidate to join the international QuNeCo project, a collaborative research initiative between leading universities in the Netherlands and Japan. As part of an interdisciplinary team, you will develop novel neuromorphic computing architectures inspired by the human brain to enable future heterogeneous computing systems with unprecedented energy efficiency and performance.

This PhD position offers the opportunity to collaborate with internationally renowned researchers, publish in leading conferences and journals, and gain experience in architecture design, hardware implementation, FPGA prototyping, and AI applications.

What are you going to do?

As a PhD candidate, you will contribute to the design and development of next-generation neuromorphic computing systems through algorithm–hardware co-design and computing-in-memory technologies. Your research will span the complete hardware design flow, from architectural exploration to hardware prototyping and experimental evaluation.

Project website: Home | QuNeCo

Your responsibilities include:

• Designing novel neuromorphic computing architectures based on application requirements and heterogeneous computing use cases.
• Investigating emerging memory technologies, including SRAM, RRAM, MRAM, and FeRAM, for efficient neuromorphic hardware implementations.
• Developing RTL implementations of neuromorphic architectures using hardware description languages and validating their functionality through simulation.
• Evaluating performance, energy efficiency, and scalability using industry-standard electronic design automation (EDA) tools.
• Developing representative AI and neuromorphic applications to demonstrate the proposed architectures.
• Prototyping hardware accelerators on FPGA platforms and integrating them into heterogeneous computing systems.
• Performing comprehensive experimental evaluations and publishing research findings in leading international conferences and journals.
• Collaborating closely with project partners in the Netherlands and Japan and participating in international project meetings, workshops, and research visits.
• Contributing to teaching activities and supervising Bachelor's and Master's students where appropriate.