Individual PhD Project Information:
Host institution: KU Leuven, Belgium
Supervisory team: Prof. Maarten De Vos (PhD supervisor, KU Leuven), Prof. Silvia Budday (co-supervisor, KTH), Prof. Nele Famaey (PhD co-cupervisor, KU Leuven), Dr Maciej Malawski (secondment host, Sano).
Enrolment in Doctoral School: Enrolled in Arenberg Doctoral School for Science, Engineering & Technology (KU Leuven) and Department of Mechanical Engineering (FAU).
PhD project description:
This PhD project will focus on generating a hybrid computational model with a possible application for estimating brain age. The objectives are: 1) Exploit the synergy between model-driven and data-driven approaches to model brain activity; 2) Integrate longitudinal functional data (e.g., multiple measurements of electrophysiology) to continuously update and personalise the brain model; 3) Develop an accurate and dynamic patient risk stratification tool for patients (e.g. differentiate healthy aging and patients with neurodegenerative disorders); 4) Increase explainability of models for an improved understanding on the changes in properties of the brain under healthy aging and neurodegenerative conditions (e.g., Alzheimer and Parkinson)
A successful project will result in novel hybrid models of the brain with improved performance and reduced computational requirements, the development of a dynamic clinical tool based on longitudinal clinical functional data, and clinical support tools for health professionals.
Who are we? The STADIUS-BIOMED research group is one of the world-leading groups developing and validating AI approaches in Healthcare, with applications covering various clinical disciplines. The group is a friendly, close-knit collaborative team focused on delivering novel innovations into healthcare practice. We closely collaborate with colleagues in UZ Leuven and with various industry partners, and have prior expertise in deploying methodology in clinical applications.
Planned secondments:
- Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU): Aims to allow the DC to gain knowledge into the mechanical aspects of brain modelling, leading to integration of neuronal aspects in the hybrid modelling approach for this project.
- Sano: Allows the DC to gain more in depth knowledge on the state-of-the-art computational methods at a leading center for computational personalized medicine.