Prof Ilias Kyriazakis, Queen's University Belfast; Simon Parsons, University of Lincoln

Shape the Future of Sustainable Livestock Systems

We are seeking a skilled, ambitious, and forward thinking researcher to join a groundbreaking project developing methodologies for the holistic assessment of livestock systems. If you are driven to apply advanced AI to real world challenges, this studentship offers the perfect platform to make a meaningful impact.

Agricultural sustainability is inherently multidimensional, spanning environmental, economic, and social domains. Each domain contains multiple impact metrics — from carbon footprint and ammonia emissions to welfare outcomes and antimicrobial use. These metrics often conflict, meaning no single management strategy excels across all dimensions.

This is where sustainability multicriteria optimisation becomes transformative. It provides a structured, rigorous way to evaluate livestock systems when multiple objectives must be balanced simultaneously, revealing the most feasible and well balanced solutions.

Who We’re Looking For

You will hold a Bachelor’s degree in Statistics, Data Science, Animal Science, or Veterinary Science. A Master’s degree is an advantage. Most importantly, you are motivated to apply advanced AI and analytical tools to enhance the sustainability of food production systems — and to create solutions that genuinely matter.

Your Mission

You will develop a methodology for optimising multiple sustainability objectives within livestock systems. A system will be described by management decisions — feeding strategies, stocking density, genotype, health interventions — each influencing sustainability outcomes. Rather than collapsing these outcomes into a single score, you will treat each as a separate objective, positioning them in a multi dimensional optimisation space.

Your work will:

• Evaluate normalisation needs across sustainability dimensions using real livestock datasets.

• Select and implement optimisation approaches — from Pareto optimality to advanced methods such as genetic algorithms.

• Develop a hybrid AI framework combining machine learning with computational argumentation to both optimise and explain outcomes.

• Engage stakeholders to assess the clarity, usefulness, and real world applicability of the model.

Why This Matters

Your work will help farmers, policymakers, and industry leaders understand not just what decisions lead to sustainable outcomes, but why — empowering transparent, explainable, and future ready livestock management.