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Project The PhD project DC7 aims to develop and apply a coupled Agent-Based Model (ABM) and couple it to the Regional Flood Model (RFM) to evaluate the effect of adaptive behaviour of small and medium-sized
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combine engineering design principles with stake-holder engagement tools to support decision-making under uncertainty. Using methods like agent-based modelling, quantitative resilience and risk analysis
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to generate tools and techniques to simulate HIV infection dynamics using a multiscale agent-based modelling technique (cells, viruses, drugs, antibodies, human lymph system, seconds, days, years). This project
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agents, and lies at the intersection of social ontology, collective ethics, moral responsibility and the ethics of blame and praise. The aim of the project is first to develop a novel methodology for
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, for instance, utilise conversational agents, computer vision, mixed reality, wearables etc. Disability, Technology, and Society: Research with a sociological or anthropological focus on the use of bespoke and/or
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critical computing. High-level topics include: social identity cues in the design of LLM-based chatbots or social robots trust and reliance on conversational agents designed to be charming and disarming so
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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computing. The lab will be exploring the notion of "deceptive by design" on all fronts: social identity cues in the design of LLM-based chatbots or social robots; trust and reliance on conversational agents
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for realistic haptic control and feedback, real-time agent-based simulation for guiding optimal work task performance. Following smart serious gaming approaches, novel artificial intelligence forecasts human
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for individuals and society, guided by good ethics, sustainability, and responsibility. Education and research at RU are based on strong ties with industry and society. We emphasize interdisciplinary collaboration