Deakin-Coventry Cotutelle:  AI for agricultural adaptation and resilience

Project supervisors

Dr Bahareh Nakisa

Additional supervisors

A/Prof Robert Faggian
A/Prof Jonothan Eden (Coventry)
Prof Matthew England (Coventry)

Deakin faculty and school

Faculty of f Science, Engineering and Built Environment
School of Information Technology

Location

Deakin Melbourne Burwood Campus (Australia) and Coventry University (United Kingdom)

This scholarship is available over three years and offers:

• a stipend of £21,805 (UKRI) per annum (2026 - 2027 rate)

• at least 12 months of the total period of the program at Deakin University.
• students will be enrolled at their home institution and at their host institution and will receive a Doctoral degree from Coventry University and Deakin University.

For international students, the awardee will also receive:

• single Overseas Student Health Cover policy for the duration of the student visa.

Help shape the future of climate-resilient agriculture by using cutting-edge AI to turn complex climate extremes into powerful, real-world stories that support farmers, food systems and communities in adapting to a changing climate.

Agricultural systems are increasingly vulnerable to climate extremes such as droughts, floods and heatwaves, which are intensifying under climate change and threatening food production, land use and rural livelihoods. Yet, planning for such extremes remains a challenge because conventional climate projections often lack the spatial resolution, sectoral relevance, and narrative framing needed for effective decision-making.

Climate storylines have therefore emerged as a powerful tool for communicating climate risk and uncertainty, offering physically consistent narratives of extreme events or climate pathways. However, generating meaningful climate storylines for agriculture is challenging. Conventional climate models struggle to capture extreme events at the spatial and temporal scales relevant to farming decisions, making it difficult to construct storylines that are both scientifically robust and practically useful for agricultural planning.

This project will address the following key questions:

This PhD project is part of the Cotutelle arrangement between Coventry University, UK and Deakin University, Melbourne, Australia. The supervision team will be drawn from the two universities. This project will start at Coventry University, UK.

This exciting PhD project will develop a novel framework for generating AI-enhanced climate storylines tailored specifically to agricultural adaptation in the face of a changing climate. A talented and motivated doctoral candidate will have the opportunity to exploit recent advances in AI that present opportunities to enhance the development of storylines for agro-climatological futures. The approach will combine the latest developments in machine learning-based downscaling of the outputs of state-of-the-art global climate models alongside other AI applications to identify patterns of past and projected extremes. These data-driven storylines will be further refined through participatory co-production with agricultural stakeholders, ensuring they reflect local realities, vulnerabilities, and decision contexts. The framework will also explore the exciting potential for agentic AI to facilitate the autonomous exploration of high-resolution climate datasets to identify plausible projections of event types relevant to specific agricultural regions or stakeholder concerns.

To be eligible you must:

• be a domestic or international candidate. Domestic includes candidates with Australian Citizenship, Australian Permanent Residency or New Zealand Citizenship
• meet the PhD entry requirements of both Deakin University and Coventry University, including equivalence and English language proficiency criteria

• enrol full time

• be able to physically locate to both Coventry University (United Kingdom) and Deakin University (Australia).

Additiona criteria:

• applicants should have a strong background in Information Technology, Computer Science, Artificial Intelligence, Data Science, Machine Learning, Software Engineering, or a closely related discipline. They should be comfortable working with computational methods, data pipelines, AI-enabled systems, and ideally some combination of modelling, analytics, and human-centred system design.
• a secondary background, interest, or demonstrated exposure in climate change, environmental science, agricultural systems, sustainability, or climate adaptation would be advantageous, particularly where it relates to decision-support, scenario analysis, or the interpretation of environmental data. Candidates who can bridge technical AI capability with applied climate or environmental problem-solving will be especially well suited to the project.

Please refer to the research degree entry requirements page and Coventry University's research entry criteria page for further information.