Mathematical Ecologist

We are seeking a highly motivated PhD candidate to develop innovative data-informed mathematical models for predicting the movement of locust hopper bands. This project aims to improve our understanding of collective animal behaviour and its application in controlling locust outbreaks.

The successful applicant will work closely with our team to design, implement, and evaluate mathematical models that incorporate variation in individual animal characteristics and resource distribution. The goal is to create predictive models that can inform optimal control strategies for locust management.

• MSc degree in Mathematics, Statistics, or a related field
• Strong background in mathematical modelling and data analysis
• Excellent programming skills in languages such as Python or R
• Familiarity with machine learning techniques and data science tools

This PhD position offers a unique opportunity to contribute to cutting-edge research in mathematical ecology and data science. The successful candidate will be part of a dynamic team and have access to extensive resources, including state-of-the-art computational facilities and collaboration opportunities with national and international partners.

This project is part of the national Analytics for the Australian Grains Industry initiative, providing extended collaborative opportunities and professional development activities.