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CDTnet PhD Fellowship F5: Digital Twin Models to Infer Anatomical and Functional Parameters at Scale King's College London in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Sep 30, 2026
Country
United Kingdom
University
King's College London
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About this position
CDTnet PhD Fellowship F5 at King's College London offers a funded doctoral opportunity in cardiovascular digital twins, focused on developing methods to infer anatomical, mechanical, and electrophysiological parameters at scale.
The project sits in the School of Biomedical Engineering & Imaging Sciences and combines biomedical engineering, computational modelling, and data-driven analysis. The successful candidate will work on personalising cardiovascular digital twin models using large imaging datasets and uncertainty-aware model estimation. A major resource for the project is the UK Biobank, providing access to imaging and functional data from around 100,000 participants, along with longitudinal data to study cardiovascular ageing and disease progression.
Research themes include building population-based reference values for cardiac anatomy and function, estimating parameters such as contractility, passive stiffness, and electrical conduction properties, and exploring variation across populations, including sex- and ethnicity-related differences. The methods developed are intended to support broader CDTnet research in heart failure, arrhythmias, and valve disease, with the goal of making personalised cardiovascular modelling more scalable and clinically useful.
The fellowship includes planned secondments and training opportunities with Maastricht University (CircAdapt modelling and large-scale personalisation), University of Zagreb School of Medicine and IDIBAPS (clinical workflows and cardiovascular disease data), University of Zaragoza (integration of clinical datasets), and GE Vingmed Ultrasound in Norway (echocardiographic digital twin personalisation).
Funding: The position is funded through Horizon Europe / MSCA Marie Curie under grant agreement 101312147.
Eligibility: Applicants must have at least a bachelor degree or equivalent, be eligible for PhD enrolment at King's College London, not already hold a doctoral degree, and comply with the MSCA mobility rule. Strong English is required. Desirable experience includes computationally intensive analysis, image or bio-signal analysis, and model personalisation techniques such as parameter estimation and uncertainty quantification.
Deadline: 30 September 2026.
Apply: Submit your application through the CDTnet website at https://www.cdtnet.eu/apply-now.
Funding details
Available
What's required
Bachelor degree or equivalent is required. Applicants must be eligible to enrol in the PhD programme at King's College London, must not already hold a doctoral degree, and must satisfy the MSCA Mobility Rule by not having lived or worked in the United Kingdom for more than 12 months in the 3 years before recruitment. Desirable skills include experience with computationally intensive analysis routines, image or bio-signal analysis (for example ECG), and model personalisation methods such as parameter estimation, uncertainty quantification, and model identifiability. Excellent English is required.
How to apply
Apply online via the CDTnet application portal. Use the provided application website and follow the instructions on the CDTnet site. Review the eligibility rules carefully before submitting. Submit your application before the deadline.
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