Postdoctoral Research Associate - Biodiversity and land use modelling Job York area,York and North Yorkshire England UK

Location: York and North Yorkshire

Research Centre & Department

The Leverhulme Centre for Anthropocene Biodiversity (LCAB) is a research centre of academics from a range of disciplines collaborating to increase knowledge of how the relationship between humanity and the natural world is changing, and how we might maintain and develop a sustainable Earth and bring about positive change. The position is linked to the Department of Environment and Geography, and will be line managed by Christopher Lyon (Environment & Geography) with mentorship from Lindsey Gillson (Biology) and Pablo Cordero Garayar (Environment & Geography).

Role

The UK is facing complex challenges and opportunities for biodiversity in the face of changing agricultural policy, and climate change. The benefits and trade-offs of different ways to address these challenges are difficult to understand for land managers, policy makers, and the public. To aid understanding, you will adapt and develop an existing land use and food system modelling and decision-support tool to incorporate biodiversity and land use.

This data-driven tool provides users with a manipulatable graphical interface to explore the impact of drivers of change (e.g. climate, policy, pollution) on metrics of land use and biodiversity under different scenarios for the UK.

Key Responsibilities include:

To develop and adapt a land use and food system modelling tool to incorporate biodiversity and land-use change.
To undertake world-leading individual and collaborative research to increase the understanding of biodiversity change.
To write up research findings and disseminate through publications, presentations, and outreach.
To collaborate with other researchers to increase the effectiveness of interdisciplinary research in the Centre
To contribute to the preparation of future research proposals.
PhD in an appropriate subject area (awarded or submitted).
Proficiency in Python for scientific computing, including basic scientific libraries (e.g. Num Py, pandas).
Experience with biodiversity-related indicators (e.g. species richness, abundance-based indicators, habitat metrics).
Experience working with large environmental datasets, data techniques and quantitative models.
Familiarity with GIS is advantageous.
Ability to write up research for high profile publications and competency in presenting work at conferences/events.
Excellent communication skills with experience of engagement across disciplines and with non-academic audiences.
Ability to develop own and collaborative research, identify sources of funding and contribute to securing these with the assistance of a mentor if required.
Experience of and capacity to carry out independent and collaborative research.

Skills, Experience & Qualifications needed

Interview date: Late October 2026. The post must commence by end of January 2027.