Early Detection and Monitoring of Locust Hopper Bands
A PhD position is available in a project focused on developing data-informed mathematical models for locust hopper band movement.
The Project
This research aims to improve current models by incorporating variation of individual animal characteristics such as hunger and epigenetic phase, and resource distribution.
We will use field and laboratory observations to tune the model's parameters and validate its predictive efficacy.
Data-Driven Approach
Techniques from data science will be applied to develop data-informed models that can predict the behaviour of the bands in response to different control measures.
Collaborative Opportunities
This project is part of the national Analytics for the Australian Grains Industry initiative, providing extended collaborative opportunities and professional development activities.