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Field
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directions: Long-term Autonomy in Uncertain Environments a. Agentic Planning and Reasoning - Semantic Mission Planning with Foundation Models - Foundation models based task decomposition - Event-driven task re
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: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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explore new mathematical and computational approaches to represent such systems, drawing on ideas from stochastic processes, four-dimensional (space-time) modelling, complex systems, agent-based modelling
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how AI is changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across
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learning-based surrogates for physical systems LLMs and scientific agents – large language models that autonomously reason, plan and execute scientific workflows AI for engineering design – LLM-driven agents
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agentic software can change the way scientists interact with complex imaging pipelines – for example, by allowing users to formulate analysis tasks at a high level while software agents orchestrate
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of up to 500 ppm of NO, CO, and H2S could occur in the gas mixture and should be detected. Some applications may require the use of gaseous anaesthetic agents such as isoflurane and desflurane. This also
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prioritise RD as a mechanism for ecosystem resilience. The project will use Agent-Based Policy Modelling (ABPM) to simulate how actors such as land managers, farmers, local authorities, and conservation
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to teaching, supervision and administrative tasks at the Department. The PhD project is situated within the research area of logics for multi-agent systems, and their applications to formal verification
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how AI is changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across