Ph.D. Position, Neural Interfaces and Adaptive Sensing

Core responsibilities:

• Develop closed-loop control architectures integrating neural interfaces with robotic systems
• Establish robust organoid–machine interfaces including neural signal acquisition and real-time decoding
• Combine intelligent interfaces with bioengineered muscle actuators to create biohybrid systems
• Progress from foundational experiments to high-impact demonstrators in organoid intelligence and adaptive control

This role advances biohybrid robotics and neural interface technologies that could lead to breakthroughs in adaptive control systems and organoid intelligence, potentially enabling new approaches to human-machine integration and medical applications.

Required qualifications:

• Master's degree in biomedical engineering, neural engineering, computational neuroscience, bioengineering, or 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
• Interest in collaborative, interdisciplinary research at biology-engineering-computation interface

Benefits include:

• International, collaborative, 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