PDRA in EEO Fire Modelling(UK Visa Sponsorship)
Job Description
About the Project
This role sits within the LEMON TREE project (Land Ecosystem Models based On New Theory, observations and Experiments), an ambitious international research programme advancing how wildfires are represented in land-surface and ecosystem models.
You will join a multidisciplinary team working at the interface of fire ecology, vegetation dynamics, and climate science, helping to build a new generation of wildfire models grounded in eco-evolutionary optimality (EEO) theory. The project aims to move beyond empirical correlations and towards theory-driven, process-based understanding of fire–vegetation interactions.
UK climate and environmental research priorities
Your Role
As a PDRA in EEO Fire Modelling, you will take a lead role in extending an existing EEO modelling framework to explicitly represent wildfire dynamics. Your work will focus on developing weekly-timestep simulations of fire occurrence and behaviour, integrating ecological processes and environmental controls.
Key responsibilities include:
- Designing and implementing wildfire modules within an EEO framework
- Modelling vegetation cover, fuel accumulation, fuel moisture and burn probability
- Evaluating and optimising model performance using laboratory and field data
- Collaborating closely with modellers, experimentalists and theoreticians
- Contributing to peer-reviewed publications and project outputs
- UK Research and Innovation (UKRI)
About You
You will be a motivated and independent researcher with a strong quantitative background and a passion for understanding wildfire processes in a changing climate.
Essential experience and skills include:
- A PhD in Environmental Science, Geography, Ecology, or a closely related field (completed by start date)
- Sound understanding of environmental and ecological controls on wildfire
- Familiarity with process-based and statistical wildfire modelling approaches
- Working knowledge of eco-evolutionary optimality concepts
- Strong programming skills in R and Python
- Experience using statistical techniques for model evaluation and optimisation
- A developing publication record appropriate to career stage
- Ability to manage competing priorities and deliver to fixed project deadlines
- UK environmental science careers and skills context
Visa & Right to Work Information
Depending on the applicable Standard Occupational Classification (SOC) code, this role may be eligible for sponsorship under the Skilled Worker route. Applicants who may require sponsorship are encouraged to check eligibility independently prior to applying.
Skilled Worker visa guidance (official)
Equality, Diversity & Inclusion
The University of Reading is committed to creating a working environment where everyone feels valued and supported. We actively encourage applications from candidates who are under-represented in academia, including women, disabled people, LGBTQ+ individuals, and people from Black, Asian and minority ethnic backgrounds.
The University is proud to be:
- An Athena SWAN Charter supporter
- A Race Equality Charter member
- A Disability Confident Employer (Level 2)
- Equality Act 2010 – official guidance
Flexible working arrangements, including job-share and part-time options, will be considered where operationally feasible.
