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Field
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as part of a team translating psychological constructs into mathematical/dynamical rules driving comprehensive agent-based models incorporating disease transmission, behaviour and feedback loops
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Fusarium graminearum, the causal agent of Fusarium Head Blight (FHB), and the English grain aphid (Sitobion avenae), one of the most economically important pests of cereal crops. FHB causes substantial
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large language models, trustworthy AI, and multi-agent systems. Successful candidates will work alongside faculty and PhD students on research tasks that span model development, evaluation, and deployment
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supervisors. A wide variety of PhD projects is available; example project areas are: Human-machine teaming AI agents for air traffic control Weak signal analysis for air traffic control room situational
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to research on plant–fungal interactions, with a focus on assessing the tolerance of genome-edited rice lines to Magnaporthe oryzae, the causal agent of rice blast disease. Prior hands-on experience with rice
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clinicians. The research will involve investigating fungal cell biology, mechanisms of action of novel antifungal agents, mechanisms of antifungal resistance, and host-pathogen interactions involving A
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changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across the network
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& Agentic AI (A3) Lab, supervised by Associate Professor Behzad Bozorgtabar and co-supervised by Professor Qi Zhang. Research vision How can intelligent robots understand instructions, anticipate
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integrates Agent-Based Models, hydrological and flood models. GEB can simulate the dynamics between multiple hazard risk, how these risk impact society, vulnerability of different sectors, and how society can
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, safety, and sustainability. This project investigates how multi-objective RL can learn effective control policies that explicitly looks for equilibria against such competing requirements, while remaining