Publisher
source

Queen's University Belfast

Just Landed

Funded PhD in Trustworthy Federated Learning for Sustainable Nutrient and Carbon Management in Livestock Systems Queen's University Belfast in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Fully funded PhD studentship: all tuition fees are paid, a tax-free stipend is provided at UKRI rates for living costs, and a Research Training Support Grant of £3,000 per year is included (up to £12,000 total) plus additional support for outreach, dissemination, summer schools, research events, and development projects.

Deadline

Oct 16, 2026

Country flag

Country

United Kingdom

University

Queen's University Belfast

Social connections

How do I apply for this?

Sign in for free to reveal details, requirements, and source links.

Apply for this position

Keywords

Computer Science
Data Science
Environmental Science
Agriculture
Electrical Engineering
Remote Sensing
Mathematics
Artificial Intelligence
Computer Vision
Sustainable Agriculture
Federated Learning
Predictive Analytics
Explainable Ai
Ecological Modeling
ML

Suggested positions

About this position

Funded PhD opportunity in Trustworthy Federated Learning enabled Predictive Analytics for Sustainable Nutrient and Carbon Management in Intensive Livestock Systems at Queen’s University Belfast within the SUSTAIN CDT.

This project sits at the intersection of computer science, machine learning, artificial intelligence, data science, environmental science, and agriculture. The research will develop predictive analytics using federated learning and trustworthy AI to support sustainable nutrient and carbon management in intensive livestock systems. It will use the X10AI AGRISMART digital twin platform and combine hyperspectral drone imagery with structured and unstructured farm data, including yield, weather, farm logs, and regulatory reports.

The PhD will explore multimodal data harmonisation, summarisation with large language models, physics-informed and data-driven modelling, and privacy-preserving collaborative training across farms. Validation will focus on two applied case studies: predicting grass growth for phosphorus geo-mining and sustainable manure export, and forecasting slurry spreading windows using local soil and weather conditions.

Supervisors: Prof. Sean McLoone, Dr. Iain Gould, Dr. Shaun Coutts, and Mr Thomas Cromie (X10AI).

Funding: fully funded studentship with all PhD tuition fees paid, a tax-free stipend at UKRI rates, and a Research Training Support Grant of £3,000 per year (up to £12,000 total), plus additional support for outreach, dissemination, summer schools, research events, and development projects.

Eligibility: applicants should have at least a 2:1 honours degree in Computer Science, Engineering, or a related discipline, with strong mathematical and programming skills. A master’s degree in AI, Machine Learning, Data Science, or Control Systems is desirable. The project is especially suitable for self-driven candidates interested in interdisciplinary research, environmental sustainability, and policy/industry engagement.

How to apply: read the full instructions at the SUSTAIN CDT application page and submit your application before the deadline. Enquiries can be directed to [email protected].

Deadline: Friday, 16 October 2026 at 12:00 midday UK time.

Funding details

Fully funded PhD studentship: all tuition fees are paid, a tax-free stipend is provided at UKRI rates for living costs, and a Research Training Support Grant of £3,000 per year is included (up to £12,000 total) plus additional support for outreach, dissemination, summer schools, research events, and development projects.

What's required

Applicants must have an honours degree at minimum 2:1 in Computer Science, Engineering, or a related discipline, plus a strong mathematical background and good programming skills. A master's degree in AI, Machine Learning, Data Science, or Control Systems is desirable. The ideal candidate should be self-driven, curious, willing to work across disciplines, eager to join an interdisciplinary team, and interested in public/policy engagement and industry-facing R&D work.

How to apply

Visit https://www.sustain-cdt.ai/how-to-apply for full application instructions and submit your application through the SUSTAIN CDT process. Direct enquiries can be sent to [email protected].

More information can be found here

Ask ApplyKite AI

Start chatting
Can you summarize this position?
What qualifications are required for this position?
How should I prepare my application?