This is for a highly motivated PhD student with an interest in above- and below-ground carbon inventory, GIS and or statistical modelling.
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PhD Scholarship Opportunity - Landscape Scale Carbon Inventory
An exciting research opportunity has arisen for outstanding applicants to join a research program funded by the Cooperative Research Centre for Spatial Information entitled: “Improved high-resolution carbon accounting in diverse landscapes – landscape scale carbon inventory”
A limitation to current estimation and modelling of carbon, in either vegetation or soils, across the diverse landscapes of Australia is the availability of reliable, ground-validated data and modelled relationships between environmental factors and the quantities of carbon that are currently or potentially stored.
This project seeks to unravel these relationships across NSW landscapes to more clearly quantify and define functional relationships between key environmental factors (climate, topography, vegetation, soil type etc.). The work will enhance our fundamental understanding of these relationships and mechanisms augment and strengthen existing data layers relating to carbon storage potential and will provide a more robust basis for estimation and quantification of carbon storage to enable participation in carbon markets with a high degree of certainty.
We are looking for a highly motivated PhD student with an interest in above- and below-ground carbon inventory, GIS and or statistical modelling.
The project has a significant fieldwork component and the successful candidate is also expected to undertake analytical and statistical work. Strong motivation, willingness to work in remote areas and the capacity to work independently are important qualities.
When to apply: Scholarship applications for candidates are open until filled.
To apply or enquire: Please send an email to Associate Professor Brian Wilson with a statement of your background and interest in the project, your Curriculum Vitae, and a copy of your undergraduate academic transcripts:
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