A first assessment of the candidates will be performed at the beginning of November 2019.
The Computational Mathematics group of the University of Groningen has two four-year PhD positions on imaged-based numerical modeling of the cardiovascular system. The positions are embedded in the project "CardioZoom: High-Fidelity Cardiovascular Modeling from super-fast Magnetic Resonance Imaging", a 1.5M Euro, 5-year ERC-Starting Grant awarded to Dr Cristóbal Bertoglio by the European Research Council. Therefore, the PhD candidates will join a vibrant and collaborative research group, with access to a large, (inter)national and multidisciplinary scientific network.
Context and relevance of the project
Biophysical computational models of the cardiovascular system need to be adapted to each particular patient from clinical data. The state-of-the-art imaging method for assessing cardiovascular diseases is Magnetic Resonance Imaging (MRI), which is hence the preferred source of data for the personalization of the models. However, MRI is still not able to reliably image the kinematics of thin structures like cardiac valves and the arterial wall. Moreover, MRI measurements of the 3D kinematics of the heart are a challenging task. These restrictions hamper the clinical translation of patient-specific modeling. Therefore, a new paradigm for model personalization is urgently needed. The ambition of CardioZoom is to propose novel methods for biophysical parameter estimation in computational models of the heart, large vessels and valves using MRI data acquired in very short scan times. The approach will be based on the deep integration imaging and biophysical principles, relaxing the constraints of standard cardiovascular imaging implying long MRI scans. Extensive validations using experimental (phantom) data will be performed and tests on volunteer and patients’ data are planned. The findings of CardioZoom will allow obtaining clinically feasible, detailed characterizations of the cardiovascular system.
The goal of the proposed doctoral research is to develop robust, efficient, and flexible numerical algorithms to estimate mechanical properties of cardiovascular tissue (blood vessels, heart) from state-of-the-art MRI measurements.
The goal of the proposed doctoral research is to develop robust, efficient, and flexible numerical algorithms for estimating relevant properties of cardiac valves from state-of-the-art MRI measurements.
Therefore, the successful candidates will gain expertise in numerical mathematics, computational (fluid) mechanics, inverse problems, and medical imaging, areas where our group has a recognized international position.
The graduate school also offers training plan tailored to the background and interests of the candidate. The positions involve a small teaching load (about 0.1 FTE, which may include supervision of student projects) in topics directly related to the research project.
If you're interested to apply, full information on the vacancies can be found here