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Mining Biomedical Publications to Defeat Pandemic: Identifying Relational Knowledge between Scientific Claims

   Centre for Computational Science and Mathematical Modelling

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  Dr Xiaorui Jiang, Prof Vasile Palade  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Coventry University is inviting applications from suitably qualified graduates for a fully-funded PhD studentship. The successful candidate will join the project ‘Mining Biomedical Publications to Defeat Pandemic: Identifying Relational Knowledge between Scientific Claims’ led by Assistant Professor (Senior Lecturer) Dr Xiaorui Jiang (Natural Language Processing & Scientometrics) at Coventry University, and co-supervised by Professor Vasile Palade (Artificial Intelligence).

The Centre for Computational Science and Mathematical Modelling (formerly 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. The project is under one of its four major theme groups, Machine Learning for Computer Vision and Natural Language Processing.

We welcome qualified candidate from all over the world to apply for this post. The application deadline and interview date can be found below. The notification should be sent out within 10 workdays of the interview. 

To defeat the COVID-19 pandemic, there has been unprecedented pressure on researchers to quickly understand an explosive number of publications and find a solution within a short timescale. Existing biomedical text mining tools have not proved helpful as they only support literature browsing, searching, and recommendation.

Instead, this project aims at the challenging task of mining deep actionable scientific knowledge, i.e., concluding scientific claims around entities, such as what medical compound suppresses COVID-19 symptoms, and how vaccine protects from new variants, etc. Corroborating or contradicting relations between claims will be extracted too. Researchers reason about such knowledge to generate new knowledge. To better prepare for a potential future pandemic of coronaviruses like COVID-19, this project also tries to overcome the obstacle of (semi-)automating large-scale dataset creation, by using new strategies including self-supervised training and human-in-the-loop approach.

To achieve these objectives, this project will build on the core idea of understanding scientificality. We will embark on the first efforts in developing novel methodologies to empirically qualify phrases and sentences that are of scientific value, and from there extract evidenced scientific claims and relations between claims. With such knowledge, we foresee a new paradigm for scientific information literacy for the post-COVID world. 


The project is directed from the Research Centre for Computational Sciences and Mathematical Modelling (CSMM)

Staff from CSMM largely run the MSc Data Science and Computational Intelligence programme:

Should the PhD candidate require training on data science, artificial intelligence, and machine learning (including deep learning), then modules from this programme may be undertaken in the first year. There is also a module on Natural Language Processing (7120CEM) under development that will start running in the next academic year. 

In addition, the Centre runs activities year-round for the development of their PhD students including: the CSMM 5-minute thesis competition, thesis writing bootcamps, and round table discussions on the following topics:

  • Giving seminars.
  • Writing papers.
  • Peer reviewing an article for a journal.
  • What is a research question anyway?
  • How should I read an article – there are so many to read!
  • The importance of a good abstract.

There is of course also the main research seminar program of the centre.

The Doctoral College together with the Centre for Research Capability and Development (RECAP) will deliver a wide range of research-informed training and development initiatives for the successful PhD candidate, including the PGR Welcome Programme, PGR Development Programme, PDP (Professional Development) Programme, Research Methods Programmes, and Research Writing Support etc. RECAP supports the development of professional research skills through a combination of workshops, digital resources, reading groups, activity-based learning, peer mentoring, and 1-2-1 support.

This project will also seek cross-centre collaboration from experiences scientists with expertise in epidemiology from the Centre for Intelligent Healthcare. We are expected to collaborate at various stages of the project in dataset annotation, algorithm design (for models enhanced with biomedical knowledge) and system evaluation.

Entry criteria for applicants to PHD 

  • A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 65% mark in the project element or equivalent with a minimum 65% overall module average. 


  • A Master’s Degree in a relevant subject area will be considered as an equivalent. The Masters must have been attained with overall marks at 65%. In addition, the dissertation or equivalent element in the Masters must also have been attained with a mark at 65%.


  • 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 items for candidate specification:

  • Strong, demonstrable programming skills and good mathematical grounding are essential.
  • Experience with machine learning techniques in the context of text processing or other applications is desirable.

How to apply

To find out more about the project please contact Dr. Xiaorui Jiang at [Email Address Removed]

To apply on line please visit: 

PGR+ Project Link

All applications require full supporting documentation, and a covering letter – plus one of the following

  • For pre-determined (named) projects an up-to 2000 word supporting statement is required showing how the applicant’s expertise and interests are relevant to the project. 


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

Start date: September 2022

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

Application deadline date: 31st May 2022

Interview date: 10th June 2022

Enquiries may be addressed to: Dr. Xiaorui Jiang, [Email Address Removed]

Funding Notes

Tuition fees (International)
Living bursary
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