Students and Teaching

I am always interested in hearing from potential students. Australian PhD students must be competitive to receive funding under the Research Training Program. A variety of scholarships are available for international students. Further details on enrollment at The University of Sydney can be found below:

How to apply

Entry requirements


PhD opportunity: Maximising the resilience of pastures to grazing and extreme drought events

This project aims to address the significant knowledge gap of how species composition may change due to extreme drought, and in-turn, quantify the loss of ecosystem function resulting from species turnover. Further, this project will identify species that contribute the most to function.

L’lara, Narrabri. Photo by Kieran Shephard.

A unique combination of methods will be used: The international DroughtNet protocol will be employed, where drought will be imposed using fixed shelters that passively reduce rainfall events and remote camera traps will be used as phenocams to quantify the loss of gross primary production in pastures after an extreme drought event. Results from this study will provide land managers, in both the agricultural and environmental sectors, the critical knowledge of how natural and human-modified systems will be impacted by more frequent and extreme drought events in order to maintain food security and biodiversity.

The project has financial support from the Hermon Slade Foundation and in-kind support from the Sydney Institute of Agriculture.

Project start either late 2019 or beginning of 2020 for three years.

Please email an expression of interest, including CV to Dr Aaron Greenville, School of Life and Environmental Sciences, University of Sydney

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New Honours Project 2019/2020:

Can machine learning be used to accurately identify wildlife in remote camera trap images?

Motion-active or remote camera traps are now commonly used in wildlife studies around the globe. They are a powerful and cost-effective method to survey wildlife due to their ease in deployment and ability to continually monitor populations across time. However, a common limitation of camera traps is that they capture millions of images that need to be processed visually by an observer. Machine learning techniques provide a powerful and exciting opportunity to automate image processing; thereby reducing analysis and reporting time. The time gained by implementing an automated image processing pipeline and increase speed of reporting results can be used for on-ground species conservation management.

Red-necked wallabies. Kindly provided by WildCount, Office of Environment and Heritage, NSW

This project will work closely with WildCount, a large-scale wildlife monitoring program run by the Office of Environment and Heritage, NSW Government and the School of Life and Environmental Sciences, University of Sydney. It will test the feasibility of using machine learning algorithms for identifying species in camera trap images.

Superb lyrebirds. Kindly provided by WildCount, Office of Environment and Heritage, NSW

For further information, please contact Dr Aaron Greenville, School of Life and Environmental Sciences, University of Sydney.


Teaching:

Post-graduate and academic staff:

Statistical workshops for ecology, School of Life and Environmental Sciences, University of Sydney.

This two-day workshop is designed to remove the mystery behind R, passing on tips for best practice techniques that we have picked up on our journey with R and lastly, to get you started with GLM/M and GAM/Ms. There are many ways to use R and here we wish to show you our workflow, which seems to work for us.

Undergraduate units:

2019 + School of Life and Environmental Sciences, The University of Sydney.

ENVX3001: Environmental GIS (Co-ordinator).

ENVX2001: Applied Statistical Methods.

BIOL3055: Field Studies in Biology.

ENVI1003: Global Challenges: Food, Water, Climate.

Guest lectures:

91309: Biodiversity Conservation. School of Life Science, University of Technology Sydney.

2014-2018

91120: GIS and Remote Sensing (co-ordinator). School of Life Science, University of Technology Sydney.

91309: Biodiversity Conservation. School of Life Science, University of Technology Sydney.

BIOL3007: Ecology. School of Life and Environmental Sciences, The University of Sydney.

BIOL2024: Ecology and Conservation. School of Life and Environmental Sciences, The University of Sydney.