Network inference and machine learning: understanding brain connectivity and neurological disorders

Network inference and machine learning: understanding brain connectivity and neurological disorders

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

Funding details: Bursary plus tuition fees (UK/EU/International)

Duration: Full-time – for a maximum of four years duration

Application deadline: 26th April 2021

Interview dates: Will be confirmed to shortlisted candidates

Start date: September 2021 

For queries please contact Dr Fei He


Introduction

Coventry University is inviting applications from suitably qualified graduates for a fully-funded PhD studentship. The successful candidate will join the project Network inference and machine learning: understanding brain connectivity and neurological disorders led by Senior Lecturer Dr Fei He (Machine Learning and Computational Neuroscience) at Coventry University and Dr Min Wu, at the A*STAR Institute for Infocomm Research (I2R) in Singapore.

The Centre for Data Science is a recently established research centre with a vision to become an internationally recognised research centre in the field of Artificial Intelligence and Data Science. Currently, the research themes of the centre include Machine Learning, Computational Biology and Neuroscience, Statistical and Mathematical Modelling, Wireless Sensors and the Internet-of-Things.

This research project is a collaboration between Coventry University and Singapore’s Agency for Science, Technology and Research (A*STAR). The successful candidate will have the opportunity to conduct their research project both at Coventry University, UK and for up to 2 years at the A*STAR Institute for Infocomm Research (I2R) in Singapore.

About the project

Neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD), affect tens of millions of people worldwide. Although the causes of AD and PD are still not fully understood, 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, the diagnosis of neurodegenerative diseases 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 AD and PD at the individual level. Over the last decade, electroencephalography (EEG) has emerged as an economical and non-invasive alternative technique for the study of neurodegenerative diseases. It is well-known that AD and PD patients are characterised by a reduced complexity of cortical activity and a slowing of oscillatory brain activity, therefore, it is important to study how neural activity is coordinated across different spatial and temporal scales for the diagnostic purpose. In this PhD project, we will investigate how advanced brain connectivity analysis, network inference, and machine/deep learning approaches can be used to develop new EEG-based biomarkers for the early diagnosis of neurodegenerative diseases.

This project will be based on the existing work from both UK and Singapore supervisors’ groups on computational neuroscience, nonlinear signal processing, network inference and machine learning.

Funding 

Coventry University and A*STAR jointly offer a fully-funded PhD studentship that is open  to both UK/EU and international graduates as part of the A*STAR Research Attachment Programme (ARAP).

The studentship is fully funded and will include:

  • full tuition fees
  • a stipend for up to 4 years (£15285 approx) subject to satisfactory progress
  • a one-time airfare to and from Singapore
  • a one-time settling-in allowance in Singapore
  • medical insurance for the period in Singapore
  • Conference allowances.

Benefits

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.

Other Benefits

Candidate specification

Entry Requirements

  • A minimum of a 2:1 undergraduate degree in Mathematics/Statistics, Computer Science, Engineering, Computational Biology/Neuroscience or a related discipline with a minimum 60% mark in the project
  • In the event of a undergraduate degree classification of less than 2:1, a Master’s Degree in a relevant subject area as mentioned above will be considered as an equivalent;
  • The Masters must have been attained with minimum overall marks at merit level (60%). In addition, the dissertation or equivalent element in the Masters must also have been attained with a minimum mark of merit level (60%);
  • Competent programming skills (in Matlab, Python, R or Julia) and experienced in mathematics/statistics and numerical analysis;
  • Interest in machine learning, mathematical modelling or statistical inference, and enthusiastic to work on an inter-disciplinary research project.

Plus

  • The potential to engage in innovative research and to complete the PhD within 4 years;
  • Minimum English language proficiency of IELTS Academic 7.0 with a minimum of 6.5 in each component, if you are an EU (non UK) or overseas national.

How to apply

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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