[School of Engineering PhD Scholarships] Computational analysis of arterial haemodynamics to quantify plaque-risk using geometric archetypes

About the project

About the Project Cardiovascular disease remains one of the leading causes of death worldwide, with atherosclerosis developing preferentially in regions of arteries exposed to disturbed blood flow. While computational fluid dynamics (CFD) has transformed our understanding of arterial haemodynamics, most studies focus on individual patient anatomies, limiting the ability to identify general principles that govern disease development. This PhD project aims to move beyond patient-specific analysis towards a systematic understanding of how vascular geometry influences blood-flow behaviour and plaque formation. The project will develop a novel haemodynamic fingerprinting framework that links arterial geometry, blood-flow patterns and atherogenic risk. By generating large virtual populations of arteries with controlled geometric characteristics, the research will explore how features such as curvature, tortuosity, vessel diameter, branching angle, taper, stenosis and local dilations influence haemodynamic conditions associated with plaque development. The successful candidate will develop automated computer-aided design (CAD), geometry generation and meshing pipelines capable of creating libraries of idealised arterial geometries representing common vascular archetypes. Large-scale CFD simulations will then be performed under physiologically representative conditions to generate a comprehensive virtual cohort of arterial flow cases. Advanced data-analysis techniques, including dimensionality reduction and clustering, will be used to identify recurring flow behaviours and extract reduced-order descriptors of haemodynamic states. A central outcome of the research will be the creation of a reusable plaque-flow atlas, a systematic map linking vascular geometries to the haemodynamic environments they generate. Rather than treating haemodynamics as unique to individual anatomies, the project seeks to establish transferable haemodynamic fingerprints that can explain blood-flow behaviour across multiple arterial systems. This approach has the potential to uncover fundamental mechanistic relationships between geometry and disease that are currently obscured by traditional patient-by-patient studies. The work is primarily computational and will combine fluid mechanics, biomedical engineering, computational modelling and data science. Where suitable imaging-derived vascular geometries are available, atlas predictions will be assessed using patient-specific models to evaluate their transferability and clinical relevance. The successful candidate will join an interdisciplinary research environment spanning engineering, cardiovascular science and clinical research, with strong links to the Modelling and Simulation Centre and the British Heart Foundation Manchester Centre of Research Excellence. The project provides an outstanding opportunity to develop expertise in CFD, computational biomechanics, vascular modelling, data-driven analysis and cardiovascular research while contributing to the long-term goal of improving our mechanistic understanding of cardiovascular disease. 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 (or international equivalent) in a relevant science or engineering OR any upper-second class (2:1) honours degree and a Master’s degree at merit (or international equivalent) in a relevant science or engineering. Essential skills: • Interest in fluid mechanics and biological flows • Strong quantitative and programming skills. • Experience in CFD software. • Strong written and verbal communication skills. FSESoE

Research areas