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A Cohort of Virtual Human Atria with Personalised Electrophysiology for In-silico Prediction of Ablation and Pharmacology Therapy Outcome

   School of Engineering and Materials Science

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  Dr Caroline Roney  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Clinical motivation: Patient-specific response to drug or catheter ablation for atrial fibrillation treatment is challenging to predict. This makes it difficult to improve suboptimal treatment outcomes. One reason for this is that there are large variations in anatomy and electrophysiological properties between patients. Patient-specific simulations with personalised anatomy and electrophysiology may be used to investigate the effects of this heterogeneity and to predict outcome of different treatment approaches. We propose developing a virtual human atria cohort from extensive patient data. We will test whether the virtual cohort can act as a ground truth for signal processing algorithms, can be used for testing innovative ablation strategies, and can be used to identify potential drug targets for pharmacologically treating atrial fibrillation.

Aims: To create personalised models of atrial electrophysiology from electroanatomic mapping data, and to demonstrate that this virtual cohort can provide an in-silico test bed to predict outcome of atrial fibrillation therapies.


  1. Atrial fibrillation recordings can be used to characterise the conduction properties of atrial tissue.
  2. Computational models with personalised geometry calibrated to these conduction properties reproduce atrial fibrillation properties.
  3. Personalised models of atrial electrophysiology can be used to identify potential drug targets and develop novel ablation strategies and for treating atrial fibrillation.

Methodologies: This PhD project involves using and developing image processing and signal processing techniques; running finite element simulations; using machine learning and statistical analysis methods. The project is in collaboration with Acutus Medical (industrial supervisor, Dr Wilson Good), and will involve a research visit to their San Diego offices during the first year.


  • Available to Home & Overseas Applicants
  • This studentship is fully funded for 3 years and includes fees and a stipend based (currently £17,609 2021/2022).


  • The minimum requirement for this studentship opportunity is a good Honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
  • If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of 6.0 in Writing and 5.5 in all sections (Reading, Listening, Speaking).
  • Candidates are expected to start from October 2022

Supervisor Contact Details:

For informal enquiries about this position, please contact Dr Caroline Roney, E-mail: [Email Address Removed]

Application Method:

To apply for this studentship and for entry on to the Medical Engineering programme (Full Time) please follow the instructions detailed on the following webpage:

Research degrees in Engineering: http://www.qmul.ac.uk/postgraduate/research/subjects/engineering.html

Further Guidance: http://www.qmul.ac.uk/postgraduate/research/

Please be sure to include a reference to ‘2022 SEMS CHR’ to associate your application with this studentship opportunity.

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