"Post-Doctoral Research Assistant (PDRA) in EEO Vegetation Modelling"

University of Reading - Department of Geography & Environmental Science

Location:	Reading
Salary:	£36,636 per annum
Hours:	Full Time
Contract Type:	Fixed-Term/Contract

Placed On:	10th February 2026
Closes:	8th March 2026
Job Ref:	SRF52838

Full time, fixed term contract (12 months, with the potential for extension subject to funding)

Closing date: 23:59 on 8 March 2026

Interview date: to be confirmed

By reference to the applicable SOC code for this role, sponsorship may be possible under the Skilled Worker Route. Applicants wishing to consider the SWR must ensure that they are able to meet the points requirement before applying. There is further information about this on the UK Visas and Immigration Website.

The PDRA in EEO Vegetation Modelling will work on the LEMONTREE (Land Ecosystem Models based On New Theory, observations and Experiments) project and will be part of a team of scientists developing and testing a theoretical basis for modelling vegetation based on eco-evolutionary optimality (EEO) theory, suitable for implementation in the land-surface scheme of earth system models. The post-holder will be responsible for integrating existing EEO components into a coherent framework and advising on the implementation of this framework in the JULES and EC-LAND land-surface models. They will also be responsible for evaluating and optimising the performance of the modelling framework using field and laboratory experiments. The postholder will be based in Reading but will be expected to interact with other members of the LEMONTREE team at the Met Office in Exeter and Imperial.

The ideal candidate will have:

• A PhD in environmental science or closely related discipline by the start date of the appointment
• An understanding of eco-evolutionary optimality theory and its application to modelling
• Excellent programming skills (R, Python)
• Experience with high performance computing
• Familiarity with relevant data sources for model evaluation
• Knowledge of appropriate statistical techniques for model evaluation
• The ability to use own initiative and plan, manage and prioritise workload effectively to meet varied and strict project delivery deadlines.

The University is committed to having a diverse and inclusive workforce, supports the gender equality Athena SWAN Charter and the Race Equality Charter, and champions LGBT+ equality. We are a Disability Confident Employer (Level 2). Applications for job-share, part-time and flexible working arrangements are welcomed and will be considered in line with business needs.