|Funding for:||UK Students|
|Funding amount:||The award will cover the tuition fees at the UK/Home rate £4,694, plus a stipend of £18,200 per annum|
|Placed On:||29th March 2023|
|Closes:||27th June 2023|
Qualification: Doctor of Philosophy in Engineering (PhD)
Start date: 2nd October 2023
Funding for: 3.5 years
Supervisor: Professor Christopher James
Project Title: Using Blind Source Separation to extract biomedical signals from the brain and heart
Independent Component Analysis (ICA) is a form of Blind Source Separation (BSS), where multiple recordings of electromagnetic activity from the body are analysed to extract meaningful information to affect a diagnosis or prognosis or to understand the underlying physiology fundamentally. This studentship will progress research undertaken within the Brain and Behaviour Lab using a very novelICA framework called Spatio-Temporal ICA (ST-ICA), which uses both spatial and temporal/spectral information derived from multi-channel time- series to extract underlying sources.
When applied to the neurophysiological field, multiple underlying brain sources are targeted - this is used in the fields of brain-computer interfacing as well as in the analysis of brain signals made when investigating epilepsy.
Equally, the methods are applied to analyse biomedical images extracted via various imaging modalities, including CTs and MRIs. In this instance, functional signals are recorded from the beating heart, aiming to identify and extract abnormalities and irregularities in the beating heart.
The award will cover the tuition fees at the UK/Home rate £4,694, plus a stipend of £18,200 per annum for 3.5 years of full-time study. International candidates are welcome to apply but must meet the fee difference.
This studentship will suit anyone with an engineering/ physics/ mathematics background and a biomedical background. Biomedical engineering graduates are particularly encouraged to apply. The work involves expanding the research in the general field of blind source separation as applied to biomedical signals - most especially to neurophysiological and/or cardiac data.
Having a good background in maths and adapt-processing is important, as is the ability to code (no need to be a programmer but algorithms are at the heart of these techniques). Being familiar with Matlab is a bonus.
How to apply:
Candidates should submit an expression of interest by sending a CV and supporting statement outlining their skills and interests in this research area to www.warwick.ac.uk/engpgr/cjj/appcv/. If this initial application succeeds, we invite you to apply for study formally. All candidates must fulfil the University of Warwick entry criteria and obtain an unconditional offer before commencing enrolment.
The University of Warwick provides an inclusive working and learning environment, recognising and respecting every individual’s differences. We welcome applications from individuals who identify with any of the protected characteristics defined by the Equality Act 2010.
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