[School of Engineering PhD Scholarships] The Adapting Artery: computational and experimental digital twins of vascular remodelling

About the project

About the Project Astronauts return from six months on the International Space Station with arteries that have stiffened by the equivalent of ten to twenty years of ageing. Nobody can yet predict who will be affected, how quickly, or how best to prevent it and the same gap exists on Earth, where clinicians monitoring aneurysms or vascular ageing must rely on population statistics rather than prediction for the person in front of them. This PhD will build and validate a digital twin of the adapting artery. Starting from the group's existing patient-specific models of the carotid artery and aorta, you will add the biology: a growth-and-remodelling layer in which collagen, elastin and smooth muscle respond to their mechanical environment, so the model predicts not only how a vessel behaves today but how its properties will evolve over months in space or years of disease. You will calibrate the model on bed-rest and spaceflight ultrasound data, and you will test it properly: at the University of Southampton, together with Dr Swathi Krishna, you will run refractive-index-matched flow experiments in which laser-based imaging measures the flow inside transparent, compliant replicas of real arteries, providing direct experimental evidence that the simulations can be trusted. The validated twin will then work on two fronts at once: forecasting arterial changes over lunar and Mars mission timelines and screening exercise and lower-body negative-pressure countermeasures in silico, while the identical machinery converts aneurysm rupture-risk snapshots into growth forecasts for clinical use. This project is expected to start in September 2027. Before you apply: We strongly recommend that you contact the supervisors for this project before you apply. How to apply: To be considered for this project you must complete a formal application through our online application portal. If you already have an applicant account this link will directly open an application for PhD School of Engineering Scholarships . If you don’t already have an applicant account, please follow the instructions here. . When applying, please specify the full title and supervisor/s of the project, details of your previous study, and names and contact details of two referees. You must also upload a Supporting Statement describing the motivation to apply to the project, your CV and transcripts of awarded and in-progress university qualifications . Please note late or incomplete applications will not be considered. Equality, diversity and inclusion are fundamental to the success of The University of Manchester and central to all our activities. A diverse research community strengthens creativity, productivity and quality, while increasing the societal and economic impact of our work. We welcome applicants from all career paths, backgrounds and sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation or transgender status. We welcome applications from candidates returning to study after a career break or experience in other roles. Flexible study arrangements may be available, including part-time study at 50%, 60% or 80%, subject to the requirements of the project and funder. Eligibility : The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree in mechanical, aerospace or biomedical engineering, applied mathematics, physics or a closely related quantitative discipline (or international equivalent) OR any upper-second class (2:1) honours degree and a Master’s degree at merit in a discipline directly relevant to the PhD (or international equivalent). A solid grounding in solid and/or fluid mechanics and in numerical methods is essential, together with programming experience in C++. Prior experience of finite element analysis, computational fluid dynamics or fluid–structure interaction, continuum biomechanics, machine learning, experimental fluid mechanics (for example particle image velocimetry) or medical image analysis is desirable but not required, as full training will be provided. This project will remain open until filled. If your application is submitted by 1 st November 2026, you can expect a decision by 18 th December 2026. If your application is submitted by 15 th January 2027, you can expect a decision by 30 th March 2027. Self or externally funded students can also be considered for this project. FSESoE

Research areas