Research Associate (Fixed Term)

Applications are invited for a Research Associate to join Dr Emily Lines' UKRI Future Leaders Fellowship project "Next generation forest dynamics modelling using remote sensing data" funded by UKRI.

Traditional forest data is severely limited in both its spatiotemporal coverage and what it can measure. This project uses cutting-edge remote sensing data and modern data science techniques to generate new understanding of current and future forest functioning. Active and passive remote sensors, including terrestrial and drone laser scanning (LiDAR), and structure from motion photogrammetry, are able to capture the full three-dimensional structure of a forest to sub-cm scale as three-dimensional point clouds. These data offer new ways to understand forest structure, but their full potential as proxies for dynamics, function and diversity are not yet fully exploited. This project has collected and collated such data from thousands of trees across forest plots in Europe, and is building a massive new dataset of tree and forest structure. Some plots have been measured over multiple years, and more field surveys are planned, to capture three dimensional tree growth and forest structural change.

This role will generate new knowledge on the relationships between structure, function and diversity in European forests. The role will build on ongoing work within this project and will address this aim by 1) analysing existing data and 2) collecting and analysing additional high resolution remote sensing data. Such data are extremely complex to analyse, and the post-holder will use specially developed and tailored deep learning techniques to extract ecological information from noisy point clouds, and may need to develop further tools. The project will analyse these data to determine how trees and forests are structured across Europe, and how their three-dimensional structure affects and is affected by their productivity, carbon storage, and the diversity of both the trees and other species living in forests. New insights into how forest function and diversity is related to three-dimensional structure will bring help develop approaches to co-monitoring biodiversity, biomass and ecosystem function, crucial for understanding the value of forests for tackling both climate change and biodiversity loss. 

The successful candidate must have a PhD in ecology, environmental science, physical geography, or other relevant discipline which must be completed by start of appointment. The role requires both computational expertise and field data collection, and eligible candidates will demonstrate expertise and enthusiasm for both types of work. Candidates will be supported in training needs and will have access to generous project funds for workshops, conferences and travel. They must be highly motivated and should have excellent written, organisational and communication skills, and be able to work well as part of a team. 

Please refer to the Further Particulars for more comprehensive information on the qualifications, skills required and role duties. 

Fixed-term: The funds for this post are available for 24 months in the first instance. 

To apply online for this vacancy and to view further information about the role, please click on the apply button above.

Please quote reference LC45193 on your application and in any correspondence about this vacancy. 

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. 

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

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