This PhD studentship is part of the Marie Curie Network FairCFD.

Flow-MRI (magnetic resonance imaging) is a non-invasive imaging method that visualizes fluid flows in the body in 4D (3 spatial and 1 time dimension) without using ionizing radiation. It holds great promise for comprehensive characterization of blood velocity, particularly in the heart and major blood vessels, but is currently hindered by low signal-to-noise ratio (SNR) and low spatial resolution.

We have developed a method that assimilates sparse and noisy Flow-MRI data directly into a computational fluid dynamics (CFD) simulation. This method uses Bayesian inference, which is also known as probabilistic machine learning. The Bayesian inference code wraps around a differentiable Finite Element Method code, which combines adjoint methods with Laplace’s method to assimilate data and estimate uncertainties.

The objectives of the proposed study are to (i) extend Bayesian inference of Flow-MRI data to 4D pulsatile flows within compliant boundaries; (ii) implement, test, and validate the results with data from compliant test objects in MRI scanners; (iii) increase the image resolution and the predictive accuracy of derived information such as pressure gradients and wall shear stress, and (iv) assess the clinical relevance of this information by working with clinicians.

Applicants should have (or expect to obtain by the start date) an excellent undergraduate or masters degree (or equivalent) in fluid mechanics, applied mathematics, scientific computing, or related fields.

The applicant will have some experience with programming, e.g. with python, C++, Matlab. The applicant will have a strong background in fluid mechanics, numerical methods, PDEs, Finite Element Methods, or functional analysis.

Applicants must be in their first 4 years of their research career and have not yet been awarded a doctoral degree. The 4 years are counted from the date a degree was obtained which formally entitles one to embark on a doctorate.

According to the international mobility rules of the MSCA-DN program, the candidates must not have spent more than 12 months in the hosting country (UK), during the 36 months preceding the starting of the PhD.