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Funded Postdoc: Machine Learning in Cardiovascular Haemodynamics

CURAM's MedTrain+ is MSCA co-funded project to support 50 postdoctoral researchers in topics proposed by multiple supervisors including myself.

Outline: Hemodynamics 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. Physics Informed Neural Networks, trained using the experimental and patient data in our consortium, can address this problem. 

Full Advertisement:

https://www.universityofgalway.ie/media/researchcentres/curam/files/Advert-158-23-V.3-1.pdf

 

Duties and Responsibilities: A successful candidate will be expected to: 

  • Develop the optimal PINN architecture based on the underlying fundamental governing equations; 
  • Publish research results in reputed international scientific journals; 
  • Actively participate in international conferences and meetings; 
  • Communicate and promote the main results in lay terms through press releases and outreach activities; 
  • Carry out any administrative work associated with the program of research; 
  • Engage in the wider research and scholarly activities of the research group; 
  • Contribute to the school’s teaching, supervising, and tutoring where appropriate, provided it does not adversely impact the primary research role; 

 

Essential Qualifications: Candidates must 

  • Hold a doctoral degree in a relevant discipline (Solid Mechanics, Engineering Mechanics, Mechanical Engineering, Applied Mathematics, or closely related field); 
  • Have a proven publication record in the relevant field (like computational physics/wave phenomena/hyperelasticity, etc.); 
  • Demonstrate excellent communication and organizational skills and attention to detail; 
  • Have proven independent initiative and ability to work in a collaborative environment;  
  • Be highly motivated and passionate about advancing the field of PINNs and fluid mechanics; 
  • Be proficient in Python and Finite Element analysis using Abaqus. 

 

Desirable Qualifications: Ideally, successful candidates will have experience in at least one of the following topics: 

  • Machine learning or Deep Learning using Tensorflow; 
  • Wave propagation in soft solids; 
  • Experiments (rheometry, imaging, etc.) 

 

If you are interested in this topic and satisfy all the eligibility criteria (outlined in the link above) then please do not hesitate to email me (bharat.tripathi@universityofgalway.ie). Please use the subject “Postdoctoral application University of Galway 158-23”. 

Please apply as soon as possible, shortlisting in process.