PhD Scholarship – AI-Driven Optimisation for Sustainable Agriculture in Australia

PhD Scholarship – AI-Driven Optimisation for Sustainable Agriculture in Australia

This project develops an AI-enhanced decision support system for optimising energy use and crop yield in Australian greenhouse agriculture, using state-of-the-art machine learning and data analytic methods.

We invite applications for a fully funded PhD position focused on developing a cutting-edge, AI-enhanced decision support system for optimising energy use and crop yield in Australian greenhouse agriculture. This interdisciplinary project will synergise machine learning (ML) with plant optimisation modelling to estimate energy consumption and predict crop production under varying weather, soil conditions, and plant types.

The research will address both sustainability and productivity in controlled agricultural systems. The research will also explore interactive multi-objective optimization approaches, incorporating preference information provided by end-users.

This project is supported by the E2Crop Hub and the candidate will have opportunity to work alongside a large cohort of industry partners within the Hub. This outcome leads to the discovery of optimal greenhouse management strategies that balance energy efficiency with maximum crop yield.

Expand all sections

$35,886 per annum pro rata (full-time), for 3.5 years

Applications are now open.

2025-11-30

1

To be eligible for this scholarship you must:

  • have a first-class Honours or 2A Honours or equivalent degree in computing technologies; 
  • be an Australian citizen, Australian permanent resident or an international student meeting the minimum English language requirements; 
  • provide evidence of adequate oral and written communication skills; 
  • meet RMIT's entry requirements for the master by research degree (or master coursework including a minor thesis).

Interested candidates should contact Professor Xiaodong Li at xiaodong.li@rmit.edu.au or Professor Babak Abbasi at babak.abbasi@rmit.edu.au.

Please provide a short research proposal outlining your interest and alignment with the proposed research, and why you think you are the best candidate for this project. You should also provide a short CV, your academic transcripts, and two of your top published research papers (if any).

Impact

This project will help Australian farmers:

  • Minimise energy consumption
  • Maximise production and profitability, and
  • Tailor greenhouse design and operation to local climatic conditions.

Outcomes will directly support sustainable food production systems and the national energy transition strategy in agriculture.
 

Ideal Candidate

We are looking for a highly motivated candidate with a strong background in one or more of the following areas:

  • Machine Learning / Deep Learning
  • Optimisation under uncertainty 
  • Applied Statistics or Data Science

Essential skills:

  • Proficiency in Python, MATLAB, or R
  • Strong quantitative background
  • Passion for interdisciplinary research and sustainability

 

aboriginal flag float-start torres strait flag float-start

Acknowledgement of Country

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Sentient' by Hollie Johnson, Gunaikurnai and Monero Ngarigo.

More information