Outline: Haemodynamics modelling is essential for prognostics of cardiovascular diseases. It is conventionally simulated using finite element methods and can take days to produce high fidelity, clinically relevant predictions, which challenges their deployment. The technique of Physics Informed Neural Networks (PINNs) has since shown promising results in surrogate modelling of physical processes like elasticity, wave propagation, blood flow, etc. The aim of this project is to develop PINNs to model the blood flow in aorta to be validated using the experimental measurements like 4D flow MRI dataset or the insilico dataset.   

Qualifications: Aspiring candidates must have the motivation to work at the confluence of Mathematics, Mechanics, Statistics and Computer Science to develop novel theoretical models and numerical methods for Haemodynamics. Subject knowledge of Partial Differential Equations, Fluid Mechanics, Numerical Analysis, Python, C/C++, machine learning is desirable. Experimental skills will also be beneficial.

To Apply:  Applications, to include a    

    1. two-page CV,   
    2. motivation letter (including details of the past experience/courses relevant for this project), 
    3. contact details of two referees, and
    4. transcripts

should be sent, via e-mail (in one PDF only) to bharat.tripathi@universityofgalway.ie.   

Additional Details:
    • Under the supervision of Dr Bharat B. Tripathi and Ms. Niamh Hynes 
    • The annual value of the Scholarship is €18,500 per year. In addition, course fees will be paid by the College if not paid from another source. Students may also earn up to €6,000 per annum from other sources (Local  Authority Higher Education Grants, IRC Government of Ireland Scholarships, etc.).  
    • Start date: September 2023 and after. 
    • Interested candidates can reach out in case they have their own research ideas inline with the overall theme. 
    • Funded by AIDA

Applications are currently under review. Interested candidates can still send in their application package.