POSTDOCTORAL RESEARCH ASSISTANT

**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 include**



1. **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 initial focus will be on the effects of biodiversity on forest resilience
across tropical regions, closely collaborating with machine-learning
specialists to apply cutting-edge techniques for identifying ecosystem
functionality.





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.





**Applications for this vacancy should be made online. You will be required to
upload a CV and supporting statement as part of your application, explaining
how you meet the essential and desirable criteria for this post.**



For further guidance and support, please visit
**https://www.jobs.ox.ac.uk/how-to-apply**





**The closing date for applications is midday on 31 January 2025.**





**Interviews are anticipated to take place in February 2025, with exact dates
to be confirmed**





**Enquiries related to the recruitment process are to be directed to** **
[recruit@ouce.ox.ac.uk](mailto: recruit@ouce.ox.ac.uk)**





**We offer very generous benefits, some of which are:**



• Generous holiday allowance of 38 days including bank holidays



• Hybrid working



• Membership of the Oxford staff pension scheme



• Discounted bus travel



• Cycle loan scheme



• Plus, many other University benefits





The School of Geography and the Environment are committed to fostering a
culture of equality, diversity, and inclusion. Applications are particularly
encouraged from women, Black, and minority ethnic candidates, who are under-
represented in academic posts at Oxford. The school holds an Athena SWAN
Silver Award in recognition of its commitment to gender equality.