Stephanie O'Donnell
- @StephODonnell
- | She / Her
WILDLABS
- Department: Department of Geography
- Salary: £33,309-£40,927
- Reference: LC31692
- Category: Research
- Closing Date: 15 July 2022
- Apply here: https://www.jobs.cam.ac.uk/job/35363/
Applications are invited for a Research Associate to join Dr Emily Lines' UKRI Future Leaders Fellowship (FLF) project "Next generation forest dynamics modelling using remote sensing data". This is an interdisciplinary project at the intersection of ecology, remote sensing, and data science. The successful candidate will have experience and expertise in applied data science and machine learning, a demonstrated interest in ecology, terrestrial ecosystems and/or remote sensing of the environment, and be keen to work on complex environmental problems.
Forest ecosystems sequester one third of human-induced greenhouse gas emissions and house 80% of the Earth's terrestrial biodiversity, but face threats including a rapidly changing climate, and deforestation and degradation. Accurate monitoring of the structure and function of forests is crucial for effective understanding of change, but ground data are sparse and irregularly collected, and extracting ecologically meaningful information from remote sensing data is challenging. To advance understanding of forest structure and functioning at large spatial and long temporal scales, and to improve predictions of the future of forests, new, intelligent ways to fuse Earth Observation data with ground data and the output from forest models are needed.
The PDRA will work with a wide range of data collected and collated for Dr Lines' FLF, including extensive co-located ground inventory, Terrestrial Laser Scanning and drone remote sensing data from a range of sites across Europe, and national forest inventory datasets from several European countries. The PDRA will develop new methods to fuse these data with satellite data, and create detailed information about the spatio-temporal variation in forest structural properties across Europe. This will be used to inform new predictive modelling frameworks that flexibly incorporate the full range of data available to predict the future of European forests. The successful candidate will also participate in fieldwork within Europe, and disseminate findings through peer-reviewed publications and presentations at international conferences.
The PDRA will work closely with PI Dr Emily Lines and co-I Dr Stuart Grieve (QMUL). They will also collaborate with project partner Dr Paloma Ruiz-Benito (Universidad de Alcalá, Spain), and may undertake a visit to her group in Spain. Depending on relevance, the PDRA will also have the opportunity to regularly collaborate with researchers at the Alan Turing Institute, of which Dr Lines is a Fellow, including contributing to open-source toolkits for scientific image analysis being developed by members of the wider Turing community. The PDRA may have the opportunity to co-supervise student projects, and to collaborate on other work ongoing in the group. Please refer to the attached Further Particulars for the qualifications, skills and experience required, as well as the role key responsibilities.
Due to the collaborative nature of the position within the larger FLF project, and in line with current University working policy, the PDRA will be expected to work in-person in Cambridge.
Candidates are strongly encouraged to contact Dr Emily Lines ([email protected]) for informal discussions prior to applying.
Fixed-term: The funds for this post are available for 24 months in the first instance.
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.Please quote reference LC31692 on your application and in any correspondence about this vacancy.
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