PhD Student in computational modeling of atrial fibrillation04-02-2021
Atrial fibrillation (AF) is a major global health burden, affecting >33 million people. AF is associated with increased risk of stroke and heart failure, doubling cardiovascular morbidity and mortality. However, several limitations in AF detection, monitoring of patients diagnosed with AF and therapeutic targeting of specific components in real-life patients hinder a detailed understanding of the dynamic relationship between risk factors, AF and adverse outcomes such as stroke. Computer models offer unique advantages, including perfect control over parameters and perfect observability of all components of the system.
In this 4-year project, the PhD-candidate will join an interdisciplinary research team involving clinicians and scientists from the Depts of Cardiology, Physiology and Biochemistry at Maastricht University aiming to develop a highly innovative virtual-patient model that can simulate the clinical state (including the absence or presence of AF) during the entire lifetime of a cohort of thousands of virtual patients with minute-level resolution. He/she will continue the development of the recent proof-of-concept model, validating the model based on unique rhythm monitoring data available from clinical registries, and incorporating adverse outcomes associated with AF. The candidate will study existing clinical trials investigating different therapies in AF patients and will reproduce these in the cohort of virtual patients. Finally, he/she will employ the model to design and execute novel virtual clinical trials, providing important new insights to improve the detection and treatment of AF. Besides working in a stimulating translational research environment, the candidate will also have the opportunity to participate in a wide range of courses, as well as seminar series, workshops, etc., to advance their skills set.
The ideal candidate has successfully completed a master’s degree (or equivalent) in technical medicine, medical engineering, medicine, biomedical engineering or related disciplines. He/she has a strong intrinsic motivation to commit to an interdisciplinary 4 year PhD-program integrating computational approaches and complex clinical data. He/she also has a demonstrable interest in cardiovascular research, and an analytical mindset. Advanced knowledge of scientific English and excellent communication skills are required. Previous experience with programming and/or computational modeling, experience with clinical trials, or prior research experience in (cardiovascular) epidemiology or atrial fibrillation is considered a plus.