**Job Description**
The AI:Cybernetics lab aims to enable human-machine interfacing for robotic applications where humans and robots share control (e.g., cobots in industry and bionic limbs in health), requiring comprehensive integration of data from the user, robot, and environment using advanced AI. This specific project focuses on developing novel AI algorithms to decode human intention from electrophysiological signals for intuitive control of upper-limb prosthetic devices. It involves creating machine learning methods that combine neural signals with environmental context to enable seamless object manipulation, establishing a framework that balances human control with robotic assistance, reduces cognitive load, and maintains user agency during daily activities.
**Skills & Abilities**
• Strong programming skills (Python, MATLAB, and/or C++/C#)
• Knowledge of machine learning techniques, particularly for time-series data
• Strong analytical and problem-solving skills
• Excellent written and verbal communication skills in English
• Ability to work independently and in cross-functional teams
• Experience with processing and analysis of electrophysiological signals (advantageous)
• Experience with control theory and implementation (advantageous)
• Knowledge of rehabilitation robotics or assistive technologies (advantageous)
• Background in prosthetics, human-machine interfaces, human factors, or human-in-the-loop systems (advantageous)
**Qualifications**
Required Degree(s) in:
• Control Engineering
• Biomedical Engineering
• Robotics
• Related fields
**Experience**
Other:
• Enrollment as a Ph.D. student at the Doctoral School in Medicine, Biomedical Science and Technology is a prerequisite.
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