Determining AI-driven soil health benchmarks for UK agricultural systems PhD

Applications are invited for a funded PhD studentship through the NERC-funded CENTA Doctoral Training Partnership at Cranfield University, in collaboration with NIAB and the British Geological Survey (BGS). This project will develop and evaluate next-generation soil health metrics that provide actionable insights for sustainable arable land management. Using long-term experiments, national soil datasets, and AI-driven analytics, the research will assess soil health across agricultural systems and scales. The aim is to create robust, field-scale benchmarks that account for productivity and local environmental risks, advancing beyond current regional and climate-based approaches.

Soil health is fundamental to sustainable agricultural production, climate resilience, environmental protection, and food security. However, current approaches to assessing soil health often rely on broad regional or climate-based benchmarks that do not adequately reflect local management practices or field-specific environmental risks. Advances in environmental informatics, artificial intelligence (AI), remote sensing, and long-term soil monitoring provide new opportunities to develop more robust and actionable soil health assessments that can support sustainable land management decisions.

This PhD will develop, test, and refine soil health metrics that provide actionable insights for arable land management. Using large-scale soil, environmental, and crop performance datasets, the project will evaluate existing soil health indicators and identify opportunities for improvement. The research will combine expert knowledge with machine learning, predictive modelling, and remote sensing to create a framework for soil health assessment that accounts for productivity and field-scale environmental risks. The resulting metrics will be designed to support practical decision-making across a range of agricultural systems and scales.

The project is a CASE studentship funded through the NERC CENTA Doctoral Training Partnership and delivered in partnership with Cranfield University, NIAB, and the British Geological Survey (BGS). Cranfield University is internationally recognised for its expertise in soil science, environmental data science, and sustainable land management, and hosts the nationally important LandIS soil information system. NIAB is the UK's leading crop science organisation, providing extensive long-term agricultural experiments and farm datasets, while BGS contributes nationally significant environmental and geospatial data resources. The student will be supervised by Dr Toby Waine, Dr Daniel Simms, Dr Elizabeth Stockdale (NIAB), and Dr Ben Marchant (BGS).

The project will deliver improved methodologies for assessing soil health across arable farming systems. By integrating data from long-term experiments, national soil inventories, and farm-scale monitoring, the research will establish evidence-based soil health benchmarks and AI-enabled assessment approaches. The outcomes will improve understanding of how soil health varies across scales, support more effective land management decisions, and provide tools that can contribute to resilient food production, environmental stewardship, and future agricultural policy development.

The student will have access to unique datasets from NIAB's long-term experiments, Cranfield University's LandIS soil databases, and BGS environmental data resources. The project offers opportunities to work at the interface of soil science, agriculture, environmental informatics, and artificial intelligence. The student will collaborate closely with industry and research partners, engage with real-world agricultural challenges, attend national and international conferences, access specialist training through CENTA and partner organisations, and develop expertise in emerging applications of machine learning and Earth observation for environmental management.

The student will develop advanced skills in soil science, environmental data analysis, machine learning, geospatial modelling, remote sensing, and statistical evaluation. Experience working with large and complex datasets from national monitoring programmes and long-term field experiments will provide excellent preparation for careers in academia, environmental consultancy, agritech, government agencies, and the wider land management sector. The project will also build transferable skills in project management, scientific communication, stakeholder engagement, interdisciplinary research, and the application of AI to environmental challenges.

Entry Requirements: Applicants should have a first- or second-class UK honours degree or equivalent in a related discipline. This project would suit applicants from backgrounds including soil science, environmental science, geography, geology, earth science, ecology, hydrology, or related subjects. We welcome candidates interested in combining field and laboratory investigation with environmental data, GIS and predictive modelling. Applicants should be curious, willing to work across disciplines and comfortable developing both practical and quantitative skills. Previous experience in soil classification, programming or spatial modelling is welcome but not essential, as specialist training will be provided. Applicants should also be willing to undertake fieldwork and placement with project partners.

Funding: Sponsored by the Natural Environment Research Council (NERC) and Cranfield University through the Central England NERC Training Alliance (CENTA3), this studentship will provide a tax-free stipend at the UKRI rate (of up to £21,805) plus Home-rate tuition fees for 3.5 years. This studentship is open to both Home and international applicants. However, the studentship only covers tuition fees at the Home fee rate. International applicants are therefore responsible for covering the difference between the Home and international tuition fee rates from another source. No international fee waiver is available for this studentship.