predict and emulate human decision-making under uncertainty: learning from behavioural data, market reactions, and policy logs. By embedding this AI-driven cognition layer, we will simulate how subjective risk perceptions, strategic delays, and non-rational choices reshape contagion pathways under climate extremes. Impact: actionable uncertainty maps for resilient food supply chains and trade policies, early warning of cascading failures, and AI-augmented stress testing for global supply chains.
PhD project
While state-of-the-art shock-propagation models accurately map trade-network vulnerabilities to extreme weather events, they universally treat human responses (export bans, hoarding, strategic delays) as static heuristics, ignoring the adaptive, subjective, and often non-rational cognition that fundamentally reshapes contagion pathways under escalating climate extremes. The pivotal question is not merely which nodes fail, but how and when decision-makers perceive risk and act under deep uncertainty, and how these cognitive feedbacks amplify or dampen cascades across global food supply chains. This project tackles this by applying a foundation model, trained on behavioural experiments to emulate human decision-making in real time. You will embed this AI-driven cognition layer into a validated multiplex network framework (Fosch et al., 2026), transforming static topology into a dynamic, behaviour-aware stress-testing engine. Your technical programme spans three pillars: (1) curating and harmonising heterogeneous behavioural, trade, and climate datasets; (2) fine-tuning a transformer-based foundation model to predict subjective risk perceptions and strategic delays under uncertainty; and (3) running large-scale simulations under compound climate extremes to map non-linear cascade effects.
Applicant Profile
We are seeking highly motivated STEM graduates with excellent programming skills (Python, with familiarity in PyTorch/JAX or network libraries such as NetworkX/igraph). Prior experience in food systems or climate policy is not required, but intellectual curiosity about human-environment interactions and a passion for tackling grand societal challenges are essential.
Funding Notes
This project is part of the UNRISK CDT, which offers 15-18 fully-funded NERC studentships, covering full university tuition fees; a personal stipend at standard UKRI rates; £6000 individual research and training costs; £5000 (per student) of cohort-level training; and a ‘Flexible Fund’ for special projects.
International applicants will need to cover costs related to applying for a student visa and the international health surcharge (IHS)
Applications are open to UK and international applicants. The number of awards for international applicants is limited by UKRI rules.
More information is available on the UNRISK website: View Website
References
Diversification of global food trade partners increased inequalities in the exposure to shock risks (https://arxiv.org/abs/2603.01740).
Main supervisor university website https://environment.leeds.ac.uk/see/staff/13034/roger-cremades
