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Computational biology and gene network inference: study the effects of diurnal asymmetric warming on plant defence and growth

  • Full or part time
  • Application Deadline
    Friday, May 29, 2020
  • 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.

Plants undergo large-scale changes in gene expression (or transcriptional reprogramming) in response to pathogen infection. The magnitude and rate of transcriptional reprogramming depends on the time of day that the infection occurs. This project aims at investigating the impact of increased temperature, simulating the diurnal asymmetric warming due to climate change, on pathogen-induced changes in plant gene expression at system and network level.

Whole-transcriptome approaches to genetic analyses generate large datasets that allow us to develop gene regulatory networks (GRNs) to understand biological processes better. This systems biology approach also allows us to generate predictive models of how the GRNs may behave in different circumstances and in different plants. In this PhD project, we will limit our analysis to automatic network reconstruction from time-course mRNA data under a nonlinear dynamic systems framework.

This will be an exciting interdisciplinary project that combines systems biology, mathematical modelling, Bayesian/network inference, and machine learning techniques to provide important insights into the way in which plants respond to climate change. The data generated could identify pathways or gene targets as a starting point to develop strategies to improve crop productivity and resilience to climate change. This project will be carried out jointly in two research centres (Centre for Data Science and Centre for Sport, Exercise and Life Sciences) at Coventry University and in collaboration with the University of Cape Town.

Start Date: September 2020

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

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.

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

For further details see: https://www.coventry.ac.uk/research/research-students/making-an-application/

To find out more about the project please contact Dr Fei Hei

To apply on line please visit: https://pgrplus.coventry.ac.uk/

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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