Opportunities for students
The Chair of Digital Health with a Focus on Data Science offers Master's projects at the intersection of artificial intelligence, digital health, biomedical engineering, and neuroscience. Our projects combine wearable sensing, machine learning, neural interfaces, and human-centred experimentation to better understand human health, the brain, and behaviour in real-world settings. Students join ongoing research projects and work closely with PhD researchers and academic staff.
Projects are typically available in one or more of the following research directions:
1) Artificial Intelligence for biosignals
Apply modern machine learning and AI to decode and interpret physiological signals and human behaviour. Projects span machine learning for healthcare, foundational models, movement and EEG/EMG analysis, and human-AI collaboration.
2) Digital biomarkers and clinical translation
Develop computational methods to identify clinically meaningful biomarkers from wearable and neural recordings. Current applications include movement and gaze analysis, biomarkers in neurological disorders, and assistive technologies.
3) Neuromuscular interfaces and human motor control
Investigate how the nervous system controls movement using high-density EMG and motor unit recordings. Projects include real-time neural interfaces, neural decoding of finger forces, and analysis and tracking of motor neurons.
4) Wearable technologies and Digital Health
Develop wearable systems for monitoring human movement and physiology in everyday life. Topics include smart textiles, multimodal sensing, wearable neural interfaces, and experimental platforms for ecological movement analysis.
Individual projects have different requirements. Some focus primarily on programming and ML/AI, while others involve hardware development, wearable sensing, or experimental studies with human participants.
Are you interested?
The list of available projects is updated regularly and evolves together with our ongoing research. If you are interested in joining the lab, please contact us (faisal_lab@uni-bayreuth.de - more emails in the Team page) with a short description of your background and research interests. We will be happy to discuss current project opportunities and identify a topic that matches your skills and interests.