As a PhD candidate, you will join the Artificial Cognitive Systems group within the Department of Machine Learning and Neural Computing at the Donders Institute for Brain, Cognition and Behaviour. You will also be part of the Neural Control Project, which is a collaboration between Maastricht University and Radboud University. You will work closely with leading researchers in machine learning, neuroscience, experimental science, and clinical practice from both institutions. The project will be supervised by Dr. Yuzhen Qin, Dr. Mario Senden, Prof. Marcel van Gerven, and Prof. Rainer Goebel.
Your research will focus on developing novel AI-driven methods for modeling, estimation, and control of brain dynamics — time-dependent patterns of neural activity fundamental to brain function, behavior, and cognition. Controlled modulation of these dynamics has the potential to restore normal function and alleviate symptoms of neurological and psychiatric disorders such as Parkinson’s, epilepsy, depression, anxiety, chronic pain, and movement disorders.
By integrating dynamical systems theory and control theory with machine learning, you will work toward a generalizable, adaptive infrastructure for personalized neuromodulation. Central to this is a closed-loop system where the brain is the control target, techniques like focused ultrasound stimulation (FUS) and deep brain stimulation (DBS) act as actuators, the goal is to steer neural activity toward therapeutic or enhanced states.
Using neurobehavioral data, the system will generate individualized modulation commands applicable across multiple neuromodulation methods.
As part of the position, you will also spend 10% of your time on PhD jobs such as project support, teaching, and supervision. This may include mentoring student projects and assisting in course delivery.
Profile:
- You have a MSc. or M.Eng degree in Artificial Intelligence, Control Engineering, Biomedical Engineering, Computer Science, Physics, or a similar field
- You have a strong theoretical background with expertise in one or more of the following topics: machine learning, deep learning, neural differential equations, diffusion models, flow matching, dynamical systems theory, control theory, and model predictive control.
- You have excellent technical/computational skills, including advanced Python programming
- You are a highly motivated team player interested in multidisciplinary research in neurotechnology and the deployment of AI methods in the real world
- Expertise in the development of embedded AI solutions and software/hardware co-optimization is desirable but not required.
- You have a good command of spoken and written English.
If you are interested, please contact Yuzhen Qin: yuzhen.qin@donders.ru.nl.
