Postgraduate research opportunities Crop-agnostic radar-to-optical image synthesis and closed-loop AI decision automation for UK arable, viticulture and soft fruit production systems
ApplyKey facts
- Opens: Friday 18 September 2026
- Deadline: Friday 16 October 2026
- Number of places: 1
- Duration: 4 years
- Funding: Equipment costs, Home fee, Stipend, Travel costs
Overview
This PhD project will develop innovative AI technologies that enable continuous crop monitoring by combining optical, hyperspectral imagery and radar observations. Using different data from diverse sensors, this PhD will investigate how AI, multimodal learning and explainable machine learning can fuse information from radar, optical and hyperspectral sensors to provide reliable insights into crop condition, stress, disease risk and productivity.Eligibility
- Applicants must have Home fee status
- A minimum first-class or 2:1 Bachelor's degree or MSc with merit in a relevant subject area
- Non-native English speakers must hold a minimum qualification equivalent to IELTs 6.5. A Bachelor's or Master's degree from an English-speaking University will also be considered.
- Students must be resident in the UK for the majority of their studies, and any time spent overseas should be for the purposes of fieldwork/long-term attachment.
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Project Details
Agriculture is undergoing a digital transformation, driven by advances in Artificial Intelligence, Earth Observation and autonomous decision support technologies. However, a major challenge remains: most crop monitoring systems rely on optical imagery that becomes unusable at night or during cloudy conditions, severely limiting operational effectiveness in countries such as the UK.
The student will develop state-of-the-art machine learning and AI methods, such as transformer architectures, diffusion models and uncertainty-aware systems. These techniques will be used to get value from data, translating multimodal data into decision support and decision making for crop management in UK Agri-Tech applications. A distinctive aspect of the project is the development of fusion frameworks that enable operation capabilities regardless of cloud cover, enabling more resilient agricultural monitoring across arable farming, vineyards and soft-fruit production systems. This aligns closely with emerging trends in autonomous and intelligent agriculture.
The student will receive interdisciplinary training spanning AI, explainable AI, Earth Observation sensor modalities, remote sensing, precision agriculture and environmental monitoring. They will gain experience working with multimodal satellite, hyperspectral and radar datasets, advanced machine learning and AI methods and real-world agricultural applications, developing a highly demanded skillset at the interface between AI and sustainable food production.
Further information
This 4-year PhD programme is under the UKRI AI Centre for Doctoral Training in Sustainable Understandable agri-food Systems Transformed by Artificial Intelligence (SUSTAIN). SUSTAIN is a collaboration between the Universities of Lincoln, Aberdeen, Queen’s Belfast and 海角论坛, and focuses on the application of Artificial Intelligence (AI) to sustainable agri-food. Academic staff and partners have co-created projects based on key industry challenges, which will be shaped with your input during the first year of your PhD.
All projects will benefit from external partner involvement.
Recruitment is being co-ordinated by the University of Lincoln.
Funding details
4-year fully funded studentship funded by UK Research and Innovation (UKRI). All PhD tuition fees paid. A tax-free stipend at UKRI rates to cover living costs. A Research Training Support Grant (RTSG) of £3,000 each year to support travel, training and consumables costs (up to £12,000 in total). Additional funding is available to support outreach and dissemination, attendance at summer schools, research events, and development projects.
While there is no funding in place for opportunities marked "unfunded", there are lots of different options to help you fund postgraduate research. Visit funding your postgraduate research for links to government grants, research councils funding and more, that could be available.
Supervisors
Primary Supervisor: Dr Jaime Zabalza, University of 海角论坛
Additional Supervisor/s: Dr Gareth Norton, University of Aberdeen; Prof. Paul Murray, University of 海角论坛 and Chris Felder, CEO, LinearLabs
Apply
Applications can be made via .
Shortlisting will take place from 29 October 2026, with interviews taking place online between 23 November and 11 December 2026. Candidates will be informed of the interview outcome on 18 December 2026. Thereafter, the successful candidate will then complete and submit their application to the University of 海角论坛.
Number of places: 1
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