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Martin Lefebvre
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3 months ago
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PhD position in hardware-software co-design for bio-inspired ML models KU Leuven in Belgium
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Expired
Country
Belgium
University
KU Leuven
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About this position
KU Leuven is offering a PhD position in hardware-software co-design for bio-inspired machine learning models within the e-Media research lab, part of STADIUS and the Department of Electrical Engineering (ESAT). The project is supervised by Prof. Martin Lefebvre, with additional contact persons Prof. Bert Lagaisse and Prof. Bart Vanrumste. The research sits at the intersection of machine learning, embedded hardware, and efficient edge intelligence.
The project explores brain-inspired and bio-inspired ML approaches, with a particular focus on spiking neural networks, structural plasticity, delay plasticity, quantization, and hardware implementation. The goal is to develop models with very small compute and memory footprints while maintaining performance. Research will include training models with multiple plasticities at different timescales, comparing design trade-offs, and implementing the best-performing solutions in custom digital hardware such as FPGA and/or application-specific integrated circuits (ASICs).
Applications are especially relevant to temporal data and edge settings, including biomedical signals, brain-computer interfaces, keyword spotting, artificial cochleas, tactile sensing, predictive maintenance, and robot control. The broader aim is to enable on-device processing for resource-constrained environments and to better understand which bio-inspired mechanisms are most useful for efficient learning and inference.
Applicants should hold a Master’s degree in Engineering or a closely related area such as Electrical Engineering, Computer Science, or Artificial Intelligence. The ideal candidate is in the top 10% of their class at both MSc and BSc level, has strong ML and programming skills in Python and frameworks such as PyTorch and JAX, and has experience with embedded platforms like FPGAs or RISC-V microcontrollers. Experience with digital IC design and simulation tools is a plus. Strong English proficiency, independent research ability, critical thinking, research ethics, and teamwork skills are expected.
The position offers a PhD scholarship of up to four years, competitive salary and benefits, and full-time employment for four years with yearly evaluation. The successful candidate may earn a PhD in Engineering Technology. KU Leuven also highlights an international research environment, doctoral training at the Arenberg Doctoral School, conference opportunities, and a flexible working culture with up to 40% remote work.
Application deadline: 2026-08-31 23:59 (Europe/Brussels). Interested candidates should apply through the KU Leuven job portal and may contact the listed supervisors for additional information.
Funding details
Available
What's required
Applicants should have a Master’s degree in Engineering with a background in Electrical Engineering, Computer Science, Artificial Intelligence, or a related field. Candidates should be ranked within the top 10% of their class at MSc and BSc level and have outstanding study results. Required skills include a strong background in ML algorithms, programming experience in Python and deep learning frameworks such as PyTorch and JAX, experience with embedded platforms such as FPGAs or RISC-V microcontrollers, excellent English proficiency in speaking and writing, and strong interpersonal skills for international teamwork. Experience with digital IC simulation and design tools such as Cadence XCelium, Genus, and Innovus is a plus.
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Professors
Prof. dr. ir. at KU Leuven
United Kingdom
Research Interests
Hardware Engineering
Fpga Design
Electrical Engineering
Gpu Acceleration
Embedded System
Prof. dr. at KU Leuven
United Kingdom
Research Interests
Digital Electronics
Edge Computing
Electrical Engineering
Machine Learning
Computer Science
Prof. dr. ir. at KU Leuven
United Kingdom
Research Interests
Edge Computing
Digital Electronics
Computer Science
Electrical Engineering
Embedded System
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.