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with unprecedented detail, enabling dynamic, data-driven insight into the recoverable value of materials. Agentic AI systems will be designed to autonomously explore and propose optimal dismantling
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will be to: identify policy mechanisms that can change infrastructure affordance and lower infrastructure use develop an agent-based model that regards infrastructure as a socio-technical system reveal
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children with autism and eating behavior challenges. This research explores how large language models (LLMs), interactive robotics, and multimodal technologies can support creative expression and
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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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for a: PhD Candidate in Emotionally and Socially Aware Natural Language Processing (1.0fte) Project description Current Natural Language Processing (NLP) systems, and especially large language models
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description Current Natural Language Processing (NLP) systems, and especially large language models (LLMs), are interacting with human emotions more readily than earlier AI systems, but we still lack frameworks
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) Project description Current Natural Language Processing (NLP) systems, and especially large language models (LLMs), are interacting with human emotions more readily than earlier AI systems, but we still
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-based modelling, quantitative resilience assessment, and risk analysis to simulate and optimise resilience strategies. The framework will be tested and refined through pilot studies in collaboration with
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that the developed methods are robust, adaptable, and grounded in real-world practice. You will apply advanced techniques such as agent-based modelling, quantitative resilience assessment, and risk analysis to
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, machine learning and behavioral modeling methodologies. In the FlexMobility project we propose a holistic approach to design a public transport network that includes both traditional fixed lines and