PhD - Leuven | Just now
We invite applications for a cross-disciplinary PhD position to develop next-generation µEIT for microphysiological systems (MPS) by integrating AI-driven measurement science, MEMS, and microfluidics with imec’s microelectronics platform, delivering a scalable, high-throughput, high-resolution, label-free imaging system that enables 3D visualization of organoids and tissues and broadens applicability across diverse biomedical models. Students will gain hands-on experience in system design and optimization, signal and data analysis, and solving complex multi-physics challenges involving electrochemistry, electromagnetics, microfluidics, and biology. Real-time experimentation will be a key component, offering the chance to directly address pressing challenges in biological research.
Responsibility:
Candidate Profile:
We’re looking for a motivated student with master’s degree in Electrical/Electronic Engineering, Biomedical Engineering, Physics, Microsystems, Computer/Software Engineering, or related field. who is passionate about interdisciplinary research, with a solid understanding or strong interest in areas such as electronics, electro chemistry biotechnology, and signal & systems theory. Proficiency in MATLAB or Python is expected; experience with AI/ML & Computational modelling is welcome but not mandatory. Most importantly, we value curiosity, initiative, and the drive to work across disciplines.
This position offers the opportunity to closely connect with imec's experts from relevant disciplines, gaining access to imec’s world-class research infrastructure and benefiting from its unique interdisciplinary ecosystem. You’ll develop a future-ready skillset at the intersection of engineering and biology, with opportunities to publish, present, and contribute to high-impact biomedical innovation."
Required background: Electrical/Electronic Engineering, Biomedical Engineering, Physics, Microsystems, Computer/Software Engineering, or related field
Type of work: 50% Experiment, 40% Development, 10% literature
Supervisor: Liesbet Lagae
Co-supervisor: Dries Braeken
Daily advisor: Babu Linkoon Meenaketan, Yoke Chin Chai
The reference code for this position is 2026-166. Mention this reference code on your application form.