|Funding for:||UK Students, EU Students, International Students|
|Funding amount:||Bursary plus tuition fees (UK/EU/International equivalence)|
|Placed On:||27th March 2019|
|Closes:||3rd June 2019|
Neurodegenerative brain disorders like Parkinson’s disease (PD) and Alzheimer’s disease (AD) are affecting more than 50 million people worldwide. Early diagnosis and an accurate characterization of the disease progression can be very important for the treatment and the improvement of the patients’ life quality. Currently, PD or AD diagnosis mainly relies on mental status examinations and neuroimaging scans, which are expensive, time-consuming and sometimes inaccurate.
New cost-effective and accurate diagnosis tools and techniques are therefore urgently needed especially for the early detection and prediction of important degenerative disorders (e.g. PD or AD) at the individual level. Over the last decade, electroencephalography (EEG) has emerged as an economical and non-invasive alternative technique for the study of brain disorders. Most existing EEG-based analysis relies purely on linear connectivity, complexity or causality analysis. However, nonlinearity is a necessary condition of the highly-complex nature of brain. In this PhD project, we will investigate how novel nonlinear dynamic modelling and corresponding frequency-domain analysis as well as machine learning techniques can be used to develop new nonlinear biomarkers for the early diagnosis of important neurological disorders such as PD, AD, ataxia or epilepsy. This PhD programme will be based at the Centre of Data Science and High-Performance Computing, which is a new research centre at Coventry University. This PhD project is in collaboration with University of Sheffield and Sheffield Teaching Hospital NHS Trust.
The scholarship will pay an annual stipend at the standard UKRI rate and covers 100% tuition fees at the UK/EU/International rate for 3.5 years.
To make an enquiry about this opportunity
Email a full CV, academic transcripts, and cover letter, explaining your interest in pursuing a PhD in this area to: email@example.com with ‘PhD Application’ in the subject line.
To apply on line please visit: https://pgrplus.coventry.ac.uk/
All applications require full supporting documentation, a covering letter, plus a 2000-word supporting statement showing how the applicant’s expertise and interests are relevant to the project.
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