An efficient computational approach to guide intervention in treatment of stroke
Supervisor: Dr Alberto Marzo
Co-supervisor: Prof Richard Clayton
We are looking for a bright, enthusiastic and self-motivated PhD student to join our research group in the Department of Mechanical Engineering at the University of Sheffield.
The project will develop an efficient computational platform, validated through a small clinical study, to ultimately inform clinical decision in the treatment of stroke.
Strokes are a life-threatening medical condition that occurs when blood supply to part of the brain is compromised. Ischaemic stroke (85% of all cases) consists of a blockage of blood supply caused by a blood clot (coagulated blood). In some cases surgery is necessary to physically capture and remove the blood clot, e.g. using retrieval devices such as retrieval stents.
This is often a risky procedure as the clot might escape during the procedure occluding vessels further downstream. The procedure is influenced by many factors that are difficult to predict or analyse experimentally, including clot size and shape, its mechanical properties, the patient anatomy and the design of the retrieval device.
The aim of the project will be that of developing a numerical platform that will allow the investigation of the mutual influence of the variables at play and their influence on clinical outcome (e.g. retrieval forces, obstruction of flow towards peripheral vessels, etc.) The resulting model will be complex and involve modelling of haemodynamics, clot solid mechanics, and the interaction between the two. Using such a complex model to investigate the model parameter space would be unfeasible. Therefore one of the project objectives will be that of developing a statistical emulator of the model (novel aspect of research), using Gaussian Process approaches. The project findings and correlations will be validated through clinical data available at University Hospital of Tours, France.
The ideal candidate will be a home UK student, have a 1st class or a good 2.1 degree in mechanical engineering, bioengineering, physics, applied mathematics or a related discipline. Previous knowledge of fluid mechanics, numerical modelling and good programming skills are essential. No previous clinical or biological knowledge is required, although the candidate should demonstrate an interest in learning these aspects, and be keen on working at the interface between engineering and the life sciences.
This project will be supported by the INSIGNEO Institute for in silico Medicine. INSIGNEO is a research initiative between the Faculty of Engineering and the Faculty of Medicine at the University of Sheffield and the Sheffield Teaching Hospitals Foundation Trust. INSIGNEO intends to realise the scientific ambition behind the Virtual Physiological Human, producing a transformational impact on healthcare. While recently established, INSIGNEO is already considered one of worldwide-leading institutions in the area of in silico medicine research. For more information on INSIGNEO please see our web pages: http://www.insigneo.org/.
This studentship covers the cost of tuition fees and provides an annual tax-free stipend for 3 years at the standard UK research rate (£14,553 for 2017/18) and is restricted to home students only (see link for more information on eligibility).
For further information or clarifications about this project please contact Dr Alberto Marzo (email@example.com). The start date will be October 2017.
Closing date: 19th May 2017