The University of Adelaide is offering the Analytics for the Australian Grain Industry (AAGI) PhD Scholarships for 2025, providing an excellent opportunity for researchers to contribute to enhancing the profitability and global competitiveness of Australia's grain sector through advanced analytics.
About the AAGI Initiative
The AAGI initiative is a five-year strategic partnership (2023-2027) primarily funded by the Grains Research and Development Corporation (GRDC) with a substantial $36 million investment. Building on the previous Statistics for the Australian Grains Industry 3 (SAGI3) investment, this collaborative project brings together the University of Adelaide, Curtin University, and The University of Queensland.
With a total co-investment of $56 million from the three strategic partners, the initiative leverages machine learning, data fusion, and statistics to support grain growers in making data-driven decisions that have real-world impact on the agricultural sector.
Scholarship Details
The AAGI Scholarship Program (AU node) is funded by the Division of Research and Innovation as part of the University of Adelaide's co-investment. The program will support nine full-time PhD students commencing studies from 2025 to 2027.
Stipend: $35,300 per annum (2025 rate, tax-free, indexed annually)
Duration: Up to 3.5 years
Program: PhD
Applications Open: January 25, 2025
Applications Close: Open until filled
Eligibility Criteria
Applicants must be:
Australian citizens
Australian permanent residents
New Zealand citizens
Permanent Humanitarian Visa holders
International students who are acceptable candidates for a PhD degree at the University of Adelaide
Candidates must have a qualification equivalent to an Australian First-Class Honours degree (e.g., a prior research thesis that was at least six months of full-time credit and received an excellent mark, or a first-author publication in a peer-reviewed international journal).
Available Projects for 2025
In 2025, the program is recruiting three PhD students for the following projects:
Project 1: Unifying on-farm data and crop models to enhance tactical crop decisions
This project aims to integrate on-farm data streams with process-based crop models like APSIM through formal mathematical integration. The goal is to increase water and/or nitrogen use efficiency in Australian cropping systems using emerging data science approaches in uncertainty quantification, data assimilation, and optimization under uncertainty. The initial focus will be on informing nitrogen management decisions to address the gap in water-limited production potential.
Prerequisites: Strong quantitative skills are essential. Favorable consideration will be given to candidates with Masters or Honours degrees in Data Science, Applied Mathematics, Agricultural or Environmental Engineering, Agricultural Economics, Management, and Information Technology, or equivalent research/work experience.
Number of scholarships: Two
Contact person: Dr. Matthew Knowling
Project 2: Efficient construction and visualization of pangenomes for crops with large genomes
This project focuses on developing novel dynamic programming computational methods for pangenome assembly of diploid and polyploid crop species, benchmarking them against other methods such as graph-based approaches. Pangenomes are crucial for grains RD&E pre-breeding research as they capture the full spectrum of genetic diversity within a species, providing insights into gene presence/absence, structural variations, and evolutionary dynamics.
The project will combine algorithm development and computational programming with large population genomes. Candidates will work within a cutting-edge analytics team and collaborate with major partners including Curtin University and the University of Western Australia, with the potential to develop a practical web-based visualization tool for representing pangenome and structural variations.
Prerequisites: Strong Java programming skills are essential. Favorable consideration will be given to candidates with Masters or Honours degrees in Computer and Data Science, Applied Mathematics and Statistics, or equivalent research/work experience.
Number of scholarships: One
Contact person: Dr. Mario Fruzangohar
How to Apply
Expressions of interest should be emailed to Ms. Sandy Khor (sandy.khor@adelaide.edu.au) with the name of the scholarship in the subject heading.
Please include the following documents:
Evidence of Australian or New Zealand citizenship, or Australian permanent resident status (if applicable)
Degree certificates (testamurs)
Academic transcripts
Translations of non-English documentation
Evidence of English language proficiency
Curriculum vitae
This scholarship represents an excellent opportunity for researchers interested in agricultural data science to contribute to a nationally significant project while advancing their academic careers.
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