POSTDOCTORAL RESEARCH ASSISTANT

We are seeking

a researcher that is enthusiastic about fieldwork and with expertise in remote sensing data collection and application to assess ecological function and diversity in tropical forests.The ideal candidate will have both remote sensing skills and hands-on experience in ecological fieldwork. They will join the Biodiversity and Earth Observation Lab within the larger Biodiversity and Ecosystems Programme at the Environmental Change Institute. This position involves transdisciplinary research as part of an international collaborative programme combining Ecology and Remote Sensing to understand and quantify tropical forest responses to environmental change. The position includes several field trips across tropical regions to gather data and collaborate with local partners. Fieldwork will focus on data collection from permanent vegetation plots, capturing spectral and vegetation structure data (LiDAR) via drones, and potentially preparing workshops for collaborators in the UK and abroad.Key activities will include1.Exploring Earth Observation Sensors:Utilize the latest Earth Observation tools (e.g., high-resolution multispectral data from Planet, drone-based LiDAR) to enhance mapping of ecosystem structure, function, and biodiversity metrics.2.Drone Imagery Analysis:Collect and analyse drone imagery to map biodiversity and ecosystem conditions on a fine scale, refining and validating satellite products.3.Collaboration on Machine-Learning Models:Work with experts in machine learning and computer science to map vegetation structure (e.g., height, canopy cover) on a larger scale.4.Integration of Remote Sensing Metrics:Develop products describing ecosystem health using metrics derived from remote sensing. The successful candidate must hold, or be near completion (thesis submitted) of, a PhD in a relevant field, or have equivalent experience, and possess experience analysing ecological, Earth Observation, and other spatial datasets. Ideally, you have experience collecting ecological and remote sensing data in tropical forests. The successful candidate should have experience working with colleagues from diverse cultural and academic backgrounds, as collaboration across cultural boundaries is essential. You will have excellent communication skills, including the ability to write for publications, present research proposals and results, and represent the research group at meetings.