PhD Position in Brain-Inspired Neuromorphic Computing: FPGA-Based Framework for Real-Time Intelligence at Donders Centre for Cognition

1. Introduction

Are you passionate about brain-inspired AI and sustainable tech? As a PhD Candidate, you will design real-time FPGA-based systems that mimic neural processes, enabling intelligent, on-chip learning for edge AI. Dive into cutting-edge research on spiking neural networks, event-based sensors, and asynchronous learning. Collaborate internationally, publish your work, and inspire future minds through teaching and supervision!

2. Job description

Neuromorphic computing offers a transformative path towards energy-efficient and brain-inspired artificial intelligence by mimicking the structure and functionality of biological neural systems. To harness its potential, this research emphasises the use of field-programmable gate arrays (FPGAs) as a core hardware platform – enabling real-time, parallel, and low-latency processing. FPGAs are ideal for implementing spiking neural networks (SNNs), supporting on-chip learning and edge AI deployment. This project aims to develop a neuromorphic FPGA-based architecture integrating biologically plausible neuron and synapse models with innovative hardware-software co-design. You will lead the design of a scalable FPGA-based platform for neuromorphic inference and real-time learning.

You will further develop the framework to support multimodal data processing from event-based camera’s such as dynamic vision sensors (DVS). A key responsibility will be to explore and implement asynchronous learning algorithms, focusing on SNN few-shot, synergic (local-global) and asynchronous learning strategies suitable for real-time and embedded systems scenarios.

Finally, you will benchmark the developed system on real-world tasks such dynamic vision and speech recognition. You will be actively involved in teaching at the department, supervising BSc/MSc theses. In addition, you will write scientific articles and regularly participate in international conferences to present your research findings.

You’re invited to apply for a unique opportunity to work on the cutting edge of brain-inspired computation. You will develop fundamental insights and practical innovations in sustainable AI, focusing on real-time, low-power, on-chip and event-based learning systems implemented on reconfigurable neuromorphic platforms.

Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as a PhD candidate.

3. Profile

• You have a Master’s degree in Computer Science, Electrical Engineering, Artificial Intelligence, Embedded Systems, or a related field.
• You have a strong interest in brain-inspired/neuromorphic computing and efficient AI.
• You have experience with machine learning, neural networks (preferably spiking neural networks).
• You have practical skills in FPGA development, hardware-software co-design, and real-time or embedded AI systems.
• You have strong programming background (e.g. Python, C/C++, VHDL/Verilog) and a motivation to work across disciplines.
• You are a team player with good written and spoken English communication skills, a willingness to contribute to teaching and student supervision, and a readiness to present research internationally. 

4. We are

The Donders Institute for Brain, Cognition and Behaviour is a world-class interfaculty research centre that houses more than 700 researchers devoted to understanding the mechanistic underpinnings of the human mind. Research at the Donders Institute is focused around four themes:

1. Language and communication
2. Perception, action and control
3. Plasticity and memory
4. Neural computation and neurotechnology

Excellent, state-of-the-art research facilities are available for the broad range of neuroscience research that is being conducted at the Donders Institute. The Donders Institute has been assessed by an international evaluation committee as ‘excellent’ and recognised as a ‘very stimulating environment for top researchers, as well as for young talent’. The Donders Institute fosters a collaborative, multidisciplinary and supportive research environment with a diverse international staff. English is the lingua franca at the Institute.

You will be embedded in the Department of Machine Learning and Neural Computing (MLNC) at the Donders Centre for Cognition (DCCN) and the School of Artificial Intelligence (AI), both part of the Faculty of Social Sciences of Radboud University. MLNC is one of the founding partners of Radboud AI and the Nijmegen ELLIS Unit. 

5. We offer

• We will give you a temporary employment contract (1.0 FTE) of 1.5 years, after which your performance will be evaluated. If the evaluation is positive, your contract will be extended by 2.5 years (4-year contract).  
• You will receive a starting salary of €2,901 gross per month based on a 38-hour working week, which will increase to €3,707 in the fourth year (salary scale P).
• You will receive an 8% holiday allowance and an 8,3% end-of-year bonus. 
• We offer Dual Career Coaching. The Dual Career Coaching assists your partner via support, tools, and resources to improve their chances of independently finding employment in the Netherlands. 
• You will receive extra days off. With full-time employment, you can choose between 30 or 41 days of annual leave instead of the statutory 20. 

6. Practical information and applying

You can apply only via the button below. Address your letter of application to Mahyar Shahsavari. In the application form, you will find which documents you need to include with your application.

The first interviews will take place on 16 May, any second interview will take place on 21 May. You will preferably start your employment on 1 September.

We can imagine you're curious about our application procedure. It describes what you can expect during the application procedure and how we handle your personal data and internal and external candidates. If you wish to apply for a non-scientific position with a non-EU nationality, please take notice of the following information.