Primary supervisors:
Dr Paul Morris, Senior Clinical Lecturer, Consultant Cardiologist, FMDH
Dr Maria-Cruz Villa-Uriol, Lecturer in Computer Science, Engineering
Secondary Supervisors:
Professors Julian Gunn, Ian Halliday, Rod Hose in the Mathematical Modelling in Medicine Group, Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield and Sheffield Teaching Hospitals NHS Trust.
Project details
Ischaemic heart disease is a reduction in coronary blood flow and the leading cause of death worldwide, yet there are no methods for measuring coronary flow in routine clinical use. Recently, our research group invented, developed, validated and patented a computational fluid dynamics (CFD) based method for measuring coronary flow called virtuQ. virtuQ reconstructs three-dimensional coronary anatomy from clinical imaging data such as invasive angiography and optical coherence tomography and uses this to perform a CFD simulation to derive clinically useful physiological diagnostic parameters.
In this PhD project, the successful student will develop elements of the image reconstruction workflow and CFD simulation to analyse physiological parameters used to diagnose coronary heart disease such as blood flow, microvascular resistance and wall shear stress.
This project will suit students who are interested using engineering to improve how we assess and manage patients with heart disease. This project combines cutting edge engineering with clinical medicine and is co-supervised by an academic clinician (Dr Paul Morris) and a computer scientist and engineer (Dr Maria-Cruz Villa-Uriol). The successful candidate will work within both the Mathematical Modelling in Medicine Group within the faculty of Medicine Dentistry and Health and with the Machine Learning Group within Computer Science, Engineering.
This studentship is part of the INSIGNEO Institute for in silico medicine at The University of Sheffield. INSIGNEO is dedicated to the development, validation and use of in silico medicine technologies such as virtuQ. As a student, you will be a valued and active member. You will be part of a wider network of PhD students, to take part in seminars and events, and to meet leaders in the field.
Entry Requirements:
Candidates must have a first or upper second class honors degree in a relevant field of engineering or significant research experience. Ideally, applicants will have experience of computational fluid dynamics modelling and/or clinical image reconstruction using MatLab. Experience of using ANSYS is desirable as well as basic programming skills. Candidates will be expected to provide a convincing justification as to why they would like to undertake the project in their application statement, demonstrating any research knowledge and, if applicable, any experience relevant to the project. Previous knowledge of the clinical side of the project is not required, although the candidate should demonstrate an interest in gaining the appropriate knowledge during their PhD. Good analytical thinking and interpersonal skills are essential. Candidates must be home based students.
How to apply:
Please complete a University Postgraduate Research Application form available here: www.shef.ac.uk/postgraduate/research/apply
Please clearly state the prospective main supervisor in the respective box and select Infection, Immunity and Cardiovascular Disease as the department.
Enquiries:
Interested candidates should in the first instance contact Dr Paul Morris, Department of Infection, Immunity and Cardiovascular Disease, Faculty of Medicine Dentistry and Health, University of Sheffield; [Email Address Removed]
Proposed start date: From July 1st 2021 to (absolutely no later than) 31st October 2021
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