Research Associate (Software Engineering)

 Imperial College London's National Heart and Lung Institute seeks a Bioengineering Researcher Engineer to join the Cardiac Electro-Mechanics Research Group (www.cemrg.com). This role involves data acquisition, signal processing, image analysis, anatomical modelling, inverse problems, model surrogates & calibration and multi-scale cardiac electrophysiology modelling & simulation. The ideal candidate will work collaboratively with a team of...

 Imperial College London's National Heart and Lung Institute seeks a Bioengineering Researcher Engineer to join the Cardiac Electro-Mechanics Research Group (www.cemrg.com). This role involves data acquisition, signal processing, image analysis, anatomical modelling, inverse problems, model surrogates & calibration and multi-scale cardiac electrophysiology modelling & simulation. The ideal candidate will work collaboratively with a team of developers, remote and local cardiologists, and algorithm developers. The goal of this project is to create foetal cardiac digital twins that monitor, track, and forecast foetal electrophysiology.

In Cardiac Electro-Mechanics Research Group you will:  

Collaborate with a team of developers to design and implement software for interpreting foetal ECG signals through patient-specific cardiac models.

• Apply advanced techniques in image analysis, neural networks, and mesh operations to develop accurate algorithms for image analysis and simulating maternal and foetal hearts.
• Work closely with medical imaging and diagnostic datasets to extract essential information required for detailed heart analysis and simulations.
• Contribute to refining and improving existing software tools, ensuring robustness, efficiency, and accuracy in simulating the heart.

• PhD in applied mathematics, engineering, computer science or a closely related discipline, or equivalent research, industrial or commercial experience.


• Experience in working with medical images, building patient-specific models, running, and analysing simulations.


• Experience with medical image processing, signal processing, and mesh operations.


• Excellent collaboration and communication skills within a team-oriented environment.

Experience with machine learning libraries (PyTorch, Tensorflow or keras), emulation, Bayesian calibration and finite element models are desirable

This project is about developing a workflow to use modelling and simulation to better interpret foetal ECG’s to optimise measurements, optimise signal processing and understand the uncertainty in the analysis process.  

This is a full time position (35h/w) and 

Should you require any further details on the role please contact: Professor Steven Niederer, [email protected]

 The College is currently trialling a Work Location Framework until early 2023.  Hybrid working may be considered for this role and the role holder may be expected to work 60% or more of their time onsite, with 40% the minimum time spent onsite.  The opportunity for hybrid working will be discussed at interview