Postdoctoral Research Associate in Fetal Cardiology Computational Modelling via AI and Biomechanics Simulations

About the role:

The role will engage in translational research developing AI tools for rapid assessment of fetal heart anatomy and function from echocardiography images. It utilizes such tools to assess a type of advanced fetal heart intervention, fetal aortic valvuloplasty, where catheters are used to relieve flow obstruction in the fetal heart to avoid a progression to congenital heart malformation at birth. It will further develop a computational model for better patient selection.

What you would be doing:

Fetal heart intervention is an advanced therapy where catheters are used to manipulate hearts of unborn fetal children, to improve cardiac function and avoid fetal demise or a progression to cardiac malformation. However, a critical need is to further understand how disease and intervention affects survival, cardiac function, and cardiac growth and remodelling, and a key to advancing the effectiveness of the intervention is to use such knowledge to devise a more accurate patient selection algorithm.

Working with cardiologists across Europe, you will be

1. developing AI algorithms for rapid assessment of fetal heart anatomy and function from echocardiograms.
2. performing correlation analysis to understand key dependencies of good fetal heart growth and birth outcomes.
3. developing a predictive algorithm to more accurately select patients for the intervention.

You will be responsible for liaising with internal and external collaborators on data collation, perform model development and testing, and collecting feedback on results. There are ample opportunities to network with highly skilled AI experts and clinicians. You will also have the opportunity to co-mentor undergraduate, Masters and/or PhD students. You are further expected to publish findings, and help attract funding.

What we are looking for:

• PhD in Computer Science, Computational Bioengineering, Mechanical or Electrical Engineering
• Excellent coding skills
• Preferably a familiarity with machine learning and deep learning models, as well as a familiarity with cardiology.
• Ability to work well in a team, and coordinate team research
• Ability to mentor junior researchers
• Highly driven and proactive worker with a passionate for the academics.

What we can offer you:

• The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
• Grow your career: gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression.

Further Information

*please note, if you are yet to receive your PhD, you will be appointed at SP16 (£47,2223 pa)

This is a full-time post (35 hours per week) for 12 months in the first instance.

If you require any further details about the role, please contact: Choon Hwai Yap – c.yap@imperial.ac.uk.

Closing date: Midnight Sunday 05 July 2026 (UK time)

Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above.

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