PhD Position in Physics-Informed Machine Learning for Cardiovascular Medicine 2025

We invite applications for a fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is available to UK (Home) candidates only.

Arrhythmias are disorders of the heart’s electrical activity, often caused by complex changes in heart tissue. Understanding and treating arrhythmias effectively remains a major challenge. One promising approach is the use of digital twins—virtual models that replicate a patient’s heart using mathematical equations describing cardiac physiology and clinical data (e.g., ECGs, MRI scans). However, creating reliable digital twins remains difficult, limiting their clinical use.

In this project, you will build on our past work designing Physics-Informed Machine Learning (PIML) for cardiac digital twins. PIML is a set of new techniques that combine artificial intelligence’s (AI) ability to learn from data with mathematical descriptions. PIMLs can learn from small amounts of data and are more immune to hallucinations than conventional AI, making them exceptionally suited for biomedical applications.

You will integrate the exciting environment of the recently merged City St George’s University of London, and a vibrant multidisciplinary team of scientists, engineers, and clinicians. You will develop cutting-edge PIML methods with real-world applications in cardiovascular medicine, gaining valuable expertise in research at the intersection of AI, healthcare, and mathematical modelling.

Table of Content

• Summary
• Benefits
• Requirments
• Interview Process
• Application Deadline
• How To Apply

Summary

• Application DeadlineMay 30, 2025
• Study LevelPhD
• SponsorCity University London
• City to studyLondon
• School to studyCity University London
• Course to studyAerospace Engineering , Engineering , Mathematics and Statistics , Mechanical Engineering , Physical Sciences , Physics and Astronomy
• Eligible CountryUnited Kingdom

Benefits

The scholarship includes a competitive annual bursary of £21,237 for four years, full tuition fee coverage for UK/Home students, the opportunity to earn up to £4,300 per year through a non-compulsory teaching assistantship, and additional funding to support participation in conferences and professional development training.

Requirements

Please add only ‘Physics-Informed Machine Learning for Cardiovascular Medicine’ in the research proposal box.

Questions regarding the application portal should be directed to [email protected].

Please also email the following documents to Dr Varela:

1. A CV detailing academic qualifications, research experience, and relevant technical skills
2. A cover letter explaining your motivation for applying, relevant experience, and how your skills align with the project.

Interview Dates and Process

• Application deadline: 30 May 2025 (or until the position is filled)
• Preferred start date: July 2025 (later start dates can be considered)

Application Deadline

May 30, 2025

How To Apply

Are you qualified and interested in this opportunity? Kindly go to City University London on evision.city.ac.uk to apply

Please add only ‘Physics-Informed Machine Learning for Cardiovascular Medicine’ in the research proposal box.

Questions regarding the application portal should be directed to [email protected].

Please also email the following documents to Dr Varela:

1. A CV detailing academic qualifications, research experience, and relevant technical skills
2. A cover letter explaining your motivation for applying, relevant experience, and how your skills align with the project.

• Application deadline: 30 May 2025 (or until the position is filled)
• Preferred start date: July 2025 (later start dates can be considered)

For more details, visit City University London scholarship webpage.