Novel Information-Theoretic Causality Measure with application in Neuroscience and Dementia

Novel Information-Theoretic Causality Measure with application in Neuroscience and Dementia

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

Funding details: Bursary plus tuition fees (UK/International - including EU at international rates from September 2021)

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

Application deadline: 17 May 2021

Interview date: Will be confirmed to shortlisted candidates

Start date: September 2021

For further details contact: Professor Eun-jin Kim

DTA Future Societies PhD Studentships

This is a Doctoral Training Alliance (DTA) Future Societies fully-funded PhD studentship.

Find out more


Coventry University is inviting applications from ambitious and self-motivated candidates to undertake a PhD in statistical physics and neuroscience which is fully funded through the Doctoral Training Alliance programme.

Project details

Brains are complex information-processing organs, whose proper function in different parts (self-organisation) is indispensable for our optimal well-being. Their dysfunction due to damage to brain cells, communication problems among different parts, etc. degrades the quality of life in ageing, even leading to dementia which affects disproportionately older populations. Unfortunately, with no viable cure for treating dementia, early diagnosis of brain dysfunction is vital to promote early and optimal management for healthy/ageing of ever increasing old population.

A promising tool for elucidating how neural pathways breakdown in ageing and dementia is brain connectivity analysis, which identifies causal interactions among brain regions (causality analysis). Unfortunately, traditional causality measures may not be applicable for many cases of interest, due to the complexity and nonlinearity of the brain.

To address these challenges, we will develop a novel information-theoretical causality measure to quantify causality in stochastic models of neuroactivity, among different brain regions in health and dementia cases, develop computational methods and biomarkers to diagnose, and track disease progression for therapeutic interventions.

The Supervisory team includes Prof E. Kim  (Centre for Fluid and Complex Systems) and Dr F. He at (Centre for Data Science at Coventry University).


This is a fully-funded studentship, including tuition fees, stipend/bursary and an additional allowance of £2000 for travel and/or conferences.


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.

Beyond the university, the researcher will attend the DTA summer and autumn schools where they will benefit from intersectoral training that fosters opportunities to work with cohorts from other institutions on a nationwide platform.

Entry requirements

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)

How to apply

To find out more about the project, please contact Professor Eun-jin Kim.

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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