About the opportunity
What this programme is offering
SUSTAIN is a UKRI AI Centre for Doctoral Training focused on applying artificial intelligence and machine learning to challenges in sustainable agriculture and agri-food systems.
Doctoral researchers will develop advanced technical and analytical skills while working on research questions related to areas such as:
Soil health
Livestock sustainability
Crop monitoring
Food supply chains
Carbon farming
Climate adaptation
Animal health
Plant health
Food security
The programme brings together multiple disciplines, allowing students from relevant STEM and related backgrounds to apply AI and data-driven approaches to practical agricultural and environmental challenges.
PhD Funding and Benefits
The SUSTAIN programme provides financial support throughout the four-year doctoral programme.
Successful applicants will receive:
Full PhD tuition fees
Tax-free doctoral stipend
£3,000 per year Research Training Support Grant
Advanced multidisciplinary training
Access to research facilities and specialist expertise
Academic supervision and research development opportunities
Opportunities to work on real-world agricultural and sustainability challenges
The funding package is designed to support doctoral study as well as research and training activities throughout the programme.
Who Can Apply?
Applicants should normally hold one of the following qualifications:
A minimum 2:1 Bachelor's degree, or
A Master's degree with Merit
Relevant academic backgrounds may include:
Artificial Intelligence
Computer Science
Data Science
Biotechnology
Agriculture
Food Science
Environmental Science
Engineering
Sustainability
Other related STEM disciplines
Previous professional or academic experience in agriculture or the agri-food sector is not required. Applicants with strong backgrounds in AI, computing, data science, engineering or related disciplines may also be considered.
Available SUSTAIN PhD Research Projects
The programme offers several research projects addressing different aspects of sustainable agriculture, food systems and environmental resilience.
1. Animal and Plant Health Diagnostics Under Climate Change — Q2125
This project focuses on machine learning, parasite transmission and health prediction using datasets from smallholder farms in Africa.
The research aims to support One Health decision-making and may contribute to the development of a smartphone application.
2. AI for Sustainable Livestock Assessment — Q3452
This project explores AI-supported approaches for assessing livestock systems using multiple sustainability criteria.
3. AI for Antifungal Resistance Prediction — Q3139
This research focuses on Candida pathogenic yeast and uses sequencing, experimental data and artificial intelligence to identify resistance signatures and predict susceptibility to potential treatments.
4. Federated Learning for Sustainable Livestock Systems — Q3135
This project investigates trustworthy AI, federated learning and digital twin technologies to address sustainability challenges associated with livestock production.
Areas of interest include:
Nutrient runoff
Water pollution
Greenhouse gas emissions
5. AI for Sustainable Agri-Food Supply Chains — A2227
This project applies game-theoretic and probabilistic approaches to examine issues across food supply chains, including:
Logistics
Resource allocation
Emissions
Fairness
Resilience
Sustainability
6. Radar and Optical AI for Crop Production — S4155
This project combines radar, optical and hyperspectral data with artificial intelligence to improve agricultural monitoring and crop production.
7. ETHIO SENSE — A4156
This project focuses on smallholder farming in Ethiopia and addresses areas including:
Soil health
Carbon monitoring
Climate-smart crop production
Land degradation
Fertiliser decisions
Water management
8. AI-Enabled Carbon Farming — A4154
This research combines field observations, remote sensing and AI to estimate carbon outcomes and support climate-resilient smallholder agriculture.
9. AI-Based Pest Detection — L4153
This project develops advanced monitoring systems for sugar beet pest management.
Important: This specific project is listed as Home Students Only.
Universities and Research Environment
Research is distributed across several participating universities.
The University of Aberdeen contributes projects involving carbon farming, soil health, supply chains and climate-smart agriculture.
Queen’s University Belfast hosts projects covering animal and plant health, livestock sustainability, artificial intelligence and antifungal resistance.
The University of Lincoln contributes research involving livestock and agricultural AI.
The University of Strathclyde supports research involving remote sensing, crop monitoring and agricultural AI.
This multi-university structure gives doctoral researchers opportunities to work across disciplines and engage with research addressing practical agricultural and sustainability challenges.
How to apply