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Computational Neuroscience: Machine Learning and Nonlinear Signal Processing

  • Full or part time
  • Application Deadline
    Monday, June 03, 2019
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

About This PhD Project

Project Description

Coventry University (CU) is inviting applications from suitably-qualified graduates for a fully-funded PhD studentship.

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 project is in collaboration with University of Sheffield and Sheffield Teaching Hospital NHS Trust.

Training and Development

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.

Standard entry criteria for applicants to PhD

• A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the project element or equivalent with a minimum 60% overall module average.
the potential to engage in innovative research and to complete the PhD within a 3.5 years
• a minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component)

For further details see:

Additional specification

• Successful candidates will have at least a minimum 2:1 first degree in Computer Science, Engineering, Mathematics/Statistics, or a related discipline (and preferably a Masters degree).
• Interested in machine learning, mathematical modelling or nonlinear signal processing, and enthusiastic to work on an inter-disciplinary research project.
• Good programming skills (in Matlab, Rython, R or Julia) and strong in mathematics/statistics and numerical analysis.

How to apply

To find out more about the project please contact

To apply on line please visit:

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.

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

Application deadline: June 3rd 2019

Start date: September, 2019

Interview dates: Will be confirmed to shortlisted candidates

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