Predictive farming PhD Scholarship: improving risk management with AI-enhanced weather forecasts and crop models

This project will investigate artificial intelligence (AI) to improve weather forecasts and use crop models for making better farming decisions. The expected outcome is protocols for integrating AI-enhanced weather forecasts and crop models into farm management and planning tools. This is expected to result in farmers making more informed decisions that optimise resource use, boost crop yields, and enhance overall farm productivity and profitability while minimising environmental impact.

Scholarship includes 60-day Industry Engagement component with the industry partner and a structured professional development and training package.

Stipend of AUD $47,000 (2025 rate).
A project expense and development package of up to $13,000 per annum.
Maximum period of tenure of an award is 4 years. Periods of study already undertaken towards the degree will be deducted from the period of tenure.

To be eligible applicants must:

Have completed an Honours Degree with First Class or 2A Honours, or equivalent level, or a master’s degree with significant research component.
Have applied, or currently enrolled in the at UniSQ.
Not be receiving equivalent support providing a benefit greater than 75% of the student’s stipend rate.
Be an Australian citizen or Permanent Resident, or a New Zealand citizen.
Meet participating university PhD admission requirements.
Meet university English language requirements.
Not have previously completed a PhD.
Be able to commence the Program in the year of the offer.
Enrol as a full-time PhD student.
Be prepared to be located at the project location(s) that the host university has approved and, if required, comply with the host university’s external enrolment procedures.

To be eligible applicants must have:

A background in agriculture, meteorology, hydrology, or environmental science, with proficiency in statistical analysis and data processing.
Strong programming skills in R (preferable) and/or Python, and experience or interest in weather prediction or climate models.
Knowledge of machine learning, AI techniques, and cloud computing for data processing and model deployment.
Familiarity with crop models (APSIM, DSSAT, AquaCrop), irrigation systems, and agricultural practices is advantageous.
Strong analytical, critical thinking, and problem-solving skills, along with experience in literature review, scientific writing, and effective presentation of research findings.

To apply, please ensure you have digital copies of the below information:

Curriculum vitae; encompassing any research presentations and/or publications
Education qualifications (testamur and academic transcripts for all undergraduate and postgraduate awards)

Application must be made via the UniSQ Scholarship Application Management System by the closing date.

If you require assistance in completing your application please download the Scholarship Online Application Manual (PDF 2.14MB).

31 December 2024

For further information please view the following attachment or contact Dr. Brian Collins (brian.collins@unisq.edu.au).