About the Project
Phase-contrast magnetic resonance imaging (Flow MRI) is a powerful and non-invasive imaging technique that measures blood flow in time and space. It provides vital insights into key metrics for cardiovascular disease diagnosis and management, such as velocity, wall shear stress, and turbulence. However, its clinical application is currently severely limited by high noise (low signal-to-noise ratio) and low spatial and temporal resolution.
This project aims to overcome these critical limitations by applying advanced machine learning techniques to denoise and improve spatial resolutions. You will run high-fidelity computational fluid dynamics (CFD) simulations of blood flow through arteries and develop a cutting-edge super-resolution framework using convolutional neural networks (CNNs). The ultimate goal is to vastly improve the reliability of haemodynamic metrics derived from Flow MRI, enabling their direct use in clinic to support cardiovascular disease management.
Expected Outcomes
- Develop a novel machine learning framework for MR image super resolution using high fidelity CFD data.
- Validate the software using MRI scans of arterial flow phantoms.
- Collaborate directly with clinicians to maximise the translational and clinical impact of the research.
Training Opportunities
The student will benefit from working alongside a multidisciplinary team of engineers, scientists and clinicians. There will be opportunities for research visits to our collaborators in Europe. Training can be provided in computational fluid dynamics and machine learning.
Eligibility
Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science, mathematics or engineering related discipline.
- Demonstrated excellence in fluid mechanics, machine learning, or both.
- Experience in programming (e.g., Python, MATLAB, C++, etc).
- Strong written and verbal communication skills.
Before you apply
You must contact the supervisor for this project before you apply. Please send your CV and a paragraph about your motivation to study this PhD project to Dr Emily Manchester emily.manchester@manchester.ac.uk
Funding
This 3.5-year PhD project is fully funded by The Department of Mechanical and Aerospace Engineering; students who are eligible to pay tuition fees at the Home rate are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. We expect the stipend to increase each year.
We recommend that you apply early as the advert may be removed before the deadline. The start date is October 2026 or January 2027.
How to apply
You will need to submit an online application through our website here: https://uom.link/pgr-apply
When you apply, you will be asked to upload the following supporting documents:
- Final Transcript and certificates of all awarded university level qualifications
- Interim Transcript of any university level qualifications in progress
- CV
- You will be asked to supply contact details for two referees on the application form (please make sure that the contact email you provide is an official university/ work email address as we may need to verify the reference)
- Supporting statement: A one or two page statement outlining your motivation to pursue postgraduate research and why you want to undertake postgraduate research at Manchester, any relevant research or work experience, the key findings of your previous research experience, and techniques and skills you’ve developed. (This is mandatory for all applicants and the application will be put on hold without it.
Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.
If you have any queries regarding making an application please contact our admissions team FSE.doctoralacademy.admissions@manchester.ac.uk
Funding Notes
This 3.5-year PhD project is fully funded by The Department of Mechanical and Aerospace Engineering; students who are eligible to pay tuition fees at the Home rate are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. We expect the stipend to increase each year.
We recommend that you apply early as the advert may be removed before the deadline. The start date is October 2026 or January 2027.
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.
We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).