I can supervise a variety of projects in the following areas:
Statistical Sampling: Spatial sampling designs for environmental resources using available auxiliary information and optimisation techniques to draw informative probability samples. Possible projects include developing sampling algorithms; programming sampling algorithms and/or package design; developing/testing optimisation methods; developing/testing design-based estimation techniques; and numerical evaluation of sampling strategies on example populations.
Tree-based models: Tree-based learners are particularly useful in ensemble learning. Possible projects include using oblique trees in ensemble learning, variable importance measures, and resampling strategies for bagging and random forest.
A specific project in either area would be designed based on the prospective student's interests and background. My main interests lie in methodological development, but applied projects are also possible.
Supervisors
Primary Supervisor: Blair Robertson
Other Supervisors: Marco Reale, Chris Price
Key qualifications and skills
Basic statistics, mathematics, and programming skills.
Does the project come with funding
No - Student must be self-funded
Final date for receiving applications
Ongoing
How to apply
To apply, please email the primary supervisor.
Keywords
Sampling; optimization; Spatial Balance; Environmental Sampling; Statistical/Machine Learning
