2020 applicants
Postgraduate Research Opportunities

The impact of gene expression noise on plant fitness under stress conditions linked to climate change


Title: SCH35: The impact of gene expression noise on plant fitness under stress conditions linked to climate change.

Funding: A full Home/EU fee waiver or equivalent fee discount for overseas students  (£5,103 in 2019-20) (further fee details - international students will need to pay the balance of their fees) plus a doctoral stipend equivalent to the RCUK Minimum Doctoral Stipend (£15,285 in 2020-21).

Application deadline: Tuesday 31 March 2020

Start date: October 2020

Duration: 3 years (full time)

Location: Colchester Campus

Based in: School of Life Sciences (in collaboration with Department of Mathematical Sciences)

This opportunity is now closed. View our open opportunities.


Plants are constantly exposed to a wide range of environmental changes. Stress-related gene expression patterns are characterised by distinct transcriptional mechanisms, but may also enhance gene expression noise.

Intrinsic gene expression noise refers to variation that arises from molecular-level fluctuations, and it has been hypothesised that gene expression noise has undergone significant evolutionary drifts.

Genome-scale studies on unicellular organisms such as yeast have shown that dose-sensitive genes and proteins forming multicomponent complexes have low gene expression noise, genes responding to changes in the environment display high noise levels.

High levels of gene expression noise need to be balanced with growth-related gene expression programmes, and emerging data suggest that organisms exploit this noise to fuel phenotypic variation.

The project

We hypothesise that in plants, intrinsic gene expression noise may lead to selective advantage under stress and that the overall stochastic features of noise may provide beneficial diversity and survival under stress responses.

This PhD aims to investigate whether evolution has fine-tuned noise-generating mechanisms and genetic network architectures leading to plant diversity enhancing stress responses and survival.

We will use existing timeseries gene expression datasets to investigate the patterns of noise in Arabidopsis exposed to short term (high-light, pathogen infections) and long-term (drought, senescence) stress conditions.

Furthermore, we will identify groups of genes with high levels of inherent noise under control and stress conditions and validate whether high level of noise in specific genes is essential for survival under stress.


The award consists of a full Home/EU fee waiver or equivalent fee discount for overseas students (further fee details), a doctoral stipend equivalent to the Research Councils UK National Minimum Doctoral Stipend (£15,285 in 2020-21), plus £2,500 training bursary via Proficio funding, which may be used to cover the cost of advanced skills training including conference attendance and travel.


The ideal candidate will hold a BSc/MSc in Biology or Bioinformatics (preferably MSc).

How to apply

You can apply for this postgraduate research opportunity online.

Please include your CV, covering letter, personal statement, and transcripts of UG and Masters degrees in your application.

The University has moved to requiring only one reference for PhD applications and these can be received after a conditional offer has been made so the absence of these will not hold up the recruitment process.

Instruction to applicants

When you apply online you will be prompted to fill out several boxes in the form:

  • For "Course title" please put "Biological Sciences", tick "postgraduate research" and hit "search". This will bring up a list of matching courses, select the one marked "full time" and "PhD".
  • For "Proposed research topic or area of research" please put the title of this studentship (SCH35: The impact of gene expression noise on plant fitness under stress conditions linked to climate change)
  • For "If you have contacted a potential supervisor..." please put the name of the lead supervisor (Dr Ulrike Bechtold)

If you have any informal queries about this opportunity please email the lead supervisor, Dr Ulrike Bechtold (ubech@essex.ac.uk)

You can find the terms and conditions of this studentship here (PDF).

Student and academic working at a board together
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