EPSRC DTP Funded PhD Studentship: Aneurysm Detection and Growth Monitoring through Non-Invasive Peripheral Measurements


Swansea University – Biomedical Engineering and Computational Modelling

Biomedical Engineering and Computational Modelling: EPSRC Funded PhD Studentship: Aneurysm Detection and Growth Monitoring through Non-Invasive Peripheral Measurements: A Combination of Pulse Wave Haemodynamics and Machine Learning

Swansea University is a UK top 30 institution for research excellence (Research Excellence Framework 2014), and we are also extremely proud to be named Welsh University of the Year 2017 by The Times and Sunday Times Good University Guide.

Project start date: 1 October 2017

LocationZienkiewicz Centre for Computational Engineering, Swansea University

Project description:
This is a joint project between Swansea University, McLaren Applied Technologies, and vascular surgeons at Morriston Hospital, Swansea, funded by the EPSRC Doctoral Training Partnership. The successful candidate will work in the Biomedical Engineering Group within the Zienkiewicz Centre for Computational Engineering at Swansea University.

The PhD student will work on the development of pulse wave haemodynamics models, their numerical solution, and associated wave theory, to develop novel methods for aneurysm detection by using only non-invasive peripheral measurements. These physics-based models will then be augmented by machine-learning techniques to increase both accuracy and robustness. Finally, the student will develop methods to infer/monitor aneurysm growth from frequent semi-continuous peripheral measurements so that the predictive models can inform on intervention timing before the aneurysm ruptures.

This project has a potential to develop into a clinical screening tool where a few measurements are able to detect aneurysm location and severity. If an aneurysm is detected, a non-invasive wearable device can be used to monitor aneurysm growth for improved clinical decision-making.

Eligibility

Academic Requirements
Applicants should hold a first or upper second class honours degree (or its equivalent) in engineering, physical sciences, mathematics, physics, or computer science, or a Master’s degree in a related subject area to the project.

A good knowledge of computer programming in at least one compiled language (C, C++, or Fortran) and one interpreted language (MATLAB or Python) is essential. It is advantageous if the candidate has prior experience of working on research projects and writing scientific reports/articles.

Residency Criteria
Due to funding restrictions, this studentship is open to UK/EU candidates only.

Additional Funding Information
The studentship covers the full cost of UK/EU tuition fees, plus an annual stipend of £14,553.

For more information, please visit: https://www.epsrc.ac.uk/skills/students/help/eligibility/ 

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source: jobs.ac.uk

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