AI:X is an ambitious initiative at Aalborg University that aims to advance AI research and create real-world impact through interdisciplinary collaboration, and five labs will be initiated in 2025 with a total of 20 PhD stipends. The AI:Cybernetics Lab is part of the AI:X initiative with four PhD stipends and is a collaboration between the Department of Health Science and Technology, The Faculty of Medicine and the Department of Materials and Production, The Faculty of Engineering and Science. The four stipends are open for appointment from 1 August 2025 (or soon thereafter).

JOBBESKRIVELSE

We live in a world where robots are increasingly used in industry and healthcare but making them work naturally with humans remains a challenge. AI:Cybernetics develops a new kind of control system, where AI combines human signals (like muscle activity) with awareness of the environment (such as camera input). Imagine a robotic, prosthetic hand that automatically adjusts to the object you want to grab- without you needing to consciously control every movement. The same principle applies to robot arms helping with assembly tasks. The goal is intuitive and efficient teamwork between people and robots.
The goal of AI:Cybernetics lab is to enable human-machine interfacing for robotic applications where humans and robots share control (e.g. cobots in industry and bionic limbs in health). This requires comprehensive integration of many data sources coming from the user, robot, and environment. This challenge can be addressed only using advanced AI. This lab will develop a radically new paradigm for human control of complex robotic systems with high levels of agency and minimal cognitive effort.
The lab is looking for candidates for the following four stipends:
PhD Stipend 1: Brain-Machine Interfacing for Robotic Prostheses
Short description: This project will develop novel AI algorithms to decode human intention from electrophysiological signals (EEG, EMG) for intuitive control of upper-limb prosthetic devices. You will create machine learning methods that combine neural signals with environmental context to enable seamless object manipulation.

Specific requirements

• Master’s degree in Biomedical Engineering, Robotics or related fields
• Experience with processing and analysis of electrophysiological signals
• Strong programming skills (Python, MATLAB, and/or C++/C#)
• Knowledge of machine learning techniques, particularly for time-series data
• Background in prosthetics or human-machine interfaces is advantageous

SPECIFIC REQUIREMENTS:

• Master’s degree in Control Engineering, Biomedical Engineering, Robotics, or related fields
• Experience with control theory and implementation is advantageous
• Knowledge of rehabilitation robotics or assistive technologies
• Programming skills in C++/Python and familiarity with ROS is a plus
• Background in human factors or human-in-the-loop systems is beneficial

SPECIFIC REQUIREMENTS:

• Master’s degree in Computer Science, Robotics, or related fields
• Strong background in computer vision and sensor fusion
• Experience with deep learning frameworks (PyTorch, TensorFlow)
• Knowledge of 3D perception systems (RGB-D cameras, LiDAR)
• Familiarity with industrial robotics applications is desirable

SPECIFIC REQUIREMENTS:

• Master’s degree in AI, Robotics, or related fields
• Experience with multimodal machine learning architectures
• Strong programming skills and experience with deep learning frameworks
• Knowledge of human-robot interaction principles
• Background in transfer learning or domain adaptation is advantageous

ALL CANDIDATES SHOULD PRESENT THESE QUALIFICATIONS:

• Strong analytical and problem-solving skills
• Excellent written and verbal communication skills in English
• Ability to work independently and in cross-functional teams

Please refer the Job description for details