PhD Position, Computer Vision

Core responsibilities:

• Develop closed-loop control architectures where neural interfaces are used to drive and adapt robotic behavior
• Establish robust organoid–machine interfaces, including neural signal acquisition and real-time decoding
• Combine intelligent interfaces with bioengineered muscle actuators to create biohybrid systems that integrate sensing, computation, and movement
• Explore emerging directions in organoid intelligence, adaptive control, and biohybrid robotics with progression from foundational experiments to high-impact demonstrators

This role advances biohybrid robotics by integrating biological neural activity with robotic systems, potentially leading to breakthroughs in neural interfaces, adaptive control, and intelligent systems that could benefit medical and assistive technologies.

Required qualifications:

• Master's degree in biomedical engineering, neural engineering, computational neuroscience, bioengineering, or a related field
• Strong background in neural engineering/electrophysiology, computational neuroscience with machine learning focus, or biofabrication/tissue engineering
• Strong communication skills in English (written and spoken)
• Prior research experience demonstrated through thesis, research project, or equivalent
• Experience with academic writing or research dissemination (thesis, reports, manuscripts)
• Interest in collaborative research and motivation to work in interdisciplinary environment

Benefits include:

• International, collaborative, and curiosity-driven research environment
• Access to cutting-edge infrastructure including advanced fabrication and testing equipment
• Extensive mentoring, supervision, and career-planning support
• Opportunities for collaboration with world-leading research groups
• Networking through conferences, seminars, and research visits
• Fully funded, competitive salary