Project Description
Unravelling the causal mechanisms that link vascular function and regulation to adverse brain health outcome is crucial to improve the clinical prognosis in a.o. Alzheimer’s Disease and complex vascular surgery. Short, non-invasive (10 minutes) recordings of blood pressure, heart rate, and cerebral perfusion provide a wealth of information ranging from vascular dynamics to autonomic nervous system function, and from baroreflex function to cerebral autoregulation. This information can be used to unravel causal mechanisms, e.g., to identify effects of aging on vascular function, effects of Alzheimer’s disease on vascular function, and clinical associations of vascular function (vascular events, Alzheimer progression, and therapeutic implications). We propose to develop and apply causal discovery techniques to disentangle the many confounding variables from the key causal mechanisms behind these changes. In particular, we will adapt a multisource JCI framework for the novel CD-NOD algorithm to identify key drivers behind these non-stationary processes.
The result must be a single, coherent model that will: i) provide insights into predictors for short-term outcomes (mortality, ICU stay, delirium, stroke), ii) long term outcomes (neurological function, cognition, vascular events), and iii) guide selection of different clinical treatment alternatives. The techniques developed may translate to other areas of medical interest.
Requirements
We are looking for an ambitious, creative and enthusiastic computer scientist, biomedical engineer or data scientist. You should have a MSc degree in a relevant field, skills in developing artifical intelligence systems and text analysis. Good communication skills and programming experience, preferably in Python/C++, are essential.
Terms of employment
You will be appointed as a PhD student for four years with the standard salary and secondary conditions for PhD students in the Netherlands. Your performance will be evaluated after 1 year. The research should result in a PhD thesis and a system that will be implemented in clinical care at Radboudumc.
Application
You can already apply directly by e-mail to Dr. Jurgen Claassen. In your application include a motivation letter, your CV, list of grades and links to publications and your Master thesis or other work you have written in English.
All applications will be processed immediately upon receipt until the position has been filled.
