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PhD Studentship: Growing AI

University of Cambridge

Project Overview Resilient and productive agriculture is reliant on bespoke planning involving data-driven decisions guided by local practice, required practice, local data, such as crop yield, and global data such as commodity prices and weather predictions. Technological progress has made it possible to automatically collect a variety of sensor data and self-reported practice. The challenge is to understand how to leverage such information to design an AI-bestowed system that provides bespoke advice to the ind...

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Project Overview Resilient and productive agriculture is reliant on bespoke planning involving data-driven decisions guided by local practice, required practice, local data, such as crop yield, and global data such as commodity prices and weather predictions. Technological progress has made it possible to automatically collect a variety of sensor data and self-reported practice. The challenge is to understand how to leverage such information to design an AI-bestowed system that provides bespoke advice to the ind...

Opportunity details

Project Overview Resilient and productive agriculture is reliant on bespoke planning involving data-driven decisions guided by local practice, required practice, local data, such as crop yield, and global data such as commodity prices and weather predictions. Technological progress has made it possible to automatically collect a variety of sensor data and self-reported practice. The challenge is to understand how to leverage such information to design an AI-bestowed system that provides bespoke advice to the individual crop producing farmer about strategy and practice that will deliver a profitable and environmentally restorative farming system. This PhD position is funded and supported by a collaborative agreement between Hutchinsons and the charity LEAF (Linking Environment And Farming). Both organisations have complementary goals in terms of improving the way collected and available data is leveraged to improve farming practices. The successful candidate will have access to experts and data from these organisations, and will explore the development of a human-centred decision support system leveraging multimodal data and artificial intelligence. The ultimate goal for the project is to support farmers with individualised and actionable insights, allowing them to make informed decisions in relation to the profitability and sustainability of their farming practices. Ideal Candidate Profile We welcome applications from motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. An awareness of machine learning theory and techniques. Experience of working with large multimodal datasets. Interest in human-computer interaction and human-centred system design. Strong communication a...

Eligibility

The successful candidate will have access to experts and data from these organisations, and will explore the development of a human-centred decision support system leveraging multimodal data and artificial intelligence. Ideal Candidate Profile We welcome applications from motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. Experience of working with large multimodal datasets.

Requirements

The successful candidate will have access to experts and data from these organisations, and will explore the development of a human-centred decision support system leveraging multimodal data and artificial intelligence. Ideal Candidate Profile We welcome applications from motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. Experience of working with large multimodal datasets.

Funding and benefits

Funding eligibility: UK Students.

Required documents

CV

How to apply

Ideal Candidate Profile We welcome applications from motivated students with a strong background in engineering or computer science. To apply for this studentship, please send your two page CV and one page covering letter outlining your suitability to Per Ola Kristensson (pok21@cam.ac.uk) and John Dudley (jjd50@cam.ac.uk) to arrive no later than 5 pm BST on Friday 21 August. Applications may close early if the position is filled before this date. Please include "[CAM-GROWING-AI]" in your email subject.

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Host country/countriesUnited Kingdom
Eligible countries/nationalitiesUnited Kingdom
Study levelPhD / Doctorate
Field of studyAgriculture, Arts & Design, Computer Science, Artificial Intelligence, Engineering
Funding typeStipend
DeadlineAug 21, 2026
Academic year/intakeNot stated
Application feeCheck provider details.

Benefits

Funding eligibility: UK Students.

Eligibility summary

The successful candidate will have access to experts and data from these organisations, and will explore the development of a human-centred decision support system leveraging multimodal data and artificial intelligence. Ideal Candidate Profile We welcome applications from motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. Experience of working with large multimodal datasets.

Requirements

The successful candidate will have access to experts and data from these organisations, and will explore the development of a human-centred decision support system leveraging multimodal data and artificial intelligence. Ideal Candidate Profile We welcome applications from motivated students with a strong background in engineering or computer science. The ideal candidate will have: Strong programming and software skills. Experience of working with large multimodal datasets.

Documents required

CV

Language/test requirements

Check provider requirements for language or test requirements.

Listing-board disclaimer

Prime Scholarship Alerts is a listing board only and does not provide application procedures or guarantee scholarship awards. Verify all requirements, deadlines, fees, and application instructions through the provider before applying.

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