Nonlinear system identification and deep learning for neurodegenerative disease detection

Eligibility: UK/International (including EU) graduates with the required entry requirements

Funding details: Bursary plus tuition fees 

Duration: Full-Time – between three and three and a half years fixed term

Application deadline: 15 September 2023

Interview dates: Will be confirmed to shortlisted candidates

Start date: January 2024

To find out more about the project, please contact Dr Fei He. 

Project details

Neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD), affect tens of millions of people worldwide and cause a heavy economic burden on societies. Early diagnosis and an accurate characterization of disease progression are critical for treatment and improving patients' quality of life. However, current methods rely on expensive and time-consuming mental status examinations and neuroimaging scans, which can often be inaccurate.

There is an urgent need for cost-effective and accurate diagnostic tools for early detection of neurodegenerative diseases at the individual level. Electroencephalography (EEG) has emerged as a non-invasive and economical alternative technique for studying neurodegenerative diseases. However, current approaches rely primarily on linear single-channel or pairwise connectivity analysis, focused on selected brain regions. Evidence suggests that neurodegenerative diseases may affect widely distributed brain regions and such interconnections are nonlinear. Therefore, to improve diagnostic accuracy, it's important to study how neural activity is coordinated across different spatial and temporal scales.

In this PhD project, we aim to develop nonlinear signal processing, systems engineering, and advanced deep learning techniques, including graph neural networks, to capture spatial and temporal features of EEG signals and characterise neurodegenerative diseases. This will be based on the existing work from the PI’s groups.

Funding

Tuition fees and a bursary (£17,668 per annum). 

Benefits

The successful candidate will receive comprehensive research training including technical, personal and professional skills. 

All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities.  

Candidate specification

• area with a minimum classification of 2:1 and a minimum mark of 60% in the project element (or equivalent), or an equivalent award from an overseas institution.
  PLUS 
• the potential to engage in innovative research and to complete the PhD within 3.5 years

An adequate proficiency in English must be demonstrated by applicants whose first language is not English.  The general requirement is a minimum overall IELTS Academic score of 7.0 with a minimum of 6.5 in each of the four sections, or the TOEFL iBT test with a minimum overall score of 95 with a minimum of 21 in each of the four sections.

How to apply

To find out more about the project and how to apply please contact:

Dr Fei He at fei.he@coventry.ac.uk. Please attach your CV and degree transcripts.