Postdoc: Fire–Vegetation Modelling & Ecosystem Recovery

1000scholars; West of England; Hybrid; GBP 45,000 - 50,000; Full time

Job summary

The University of Bristol invites applications for a Postdoctoral Research Associate to work on the CoFLAME project, advancing vegetation recovery and wildfire emissions modelling. The role blends data synthesis, model development, and analysis to deliver new process-oriented insights into post-fire ecosystem dynamics under climate change.

You will join Professor Martin De Kauwe’s lab, collaborating with international partners, with hybrid working available and possible 80% time by arrangement.

Qualifications

• PhD (or soon to be awarded) in mathematics, vegetation modelling, physics, atmospheric science, or similar quantitative discipline.
• Significant experience in ecosystem, vegetation, land surface, or Earth system modelling, ideally with applications to wildfire, disturbance, or ecosystem recovery.
• Demonstrated programming/computing skills in a Unix/Linux environment.
• Strong research and publication track record (relative to career opportunity)
• Excellent verbal and written communication skills.
• Demonstrated ability to work effectively as part of a team and independently in a research environment.

Responsibilities

• Develop and apply new approaches to represent vegetation response and recovery after wildfire.
• Work at the interface of ecosystem science, Earth system modelling, and remote sensing.
• Investigate fire impacts on vegetation structure, carbon cycling, and ecosystem recovery.
• Collaborate with international partners to improve fire-vegetation representations in land surface models.

Skills

Programming

Teamwork

Communication

Research

Education

PhD (or soon to be awarded) in mathematics/vegetation modelling/physics/atmospheric science

Tools

Unix/Linux

Job description

The University of Bristol invites applications for a Postdoctoral Research Associate to work on the CoFLAME project, advancing vegetation recovery and wildfire emissions modelling. The role blends data synthesis, model development, and analysis to deliver new process-oriented insights into post-fire ecosystem dynamics under climate change.

You will join Professor Martin De Kauwe’s lab, collaborating with international partners, with hybrid working available and possible 80% time by arrangement.