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Applications are invited for a PhD studentship in the Department of Computer Science at City, University of London. The successful candidate will work on Agentic Artificial Intelligence—the next
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to understand these dynamics. This project proposes a novel pipeline of ideas to generate tools and techniques to simulate HIV infection dynamics using a multiscale agent-based modelling technique (cells, viruses
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structure. This PhD project will investigate systemic financial risks emerging from the convergence of agentic artificial intelligence and retail trading platforms. Using a combination of experimental
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costs [1]-[5]. Building on these previous findings, this PhD project will design a new MARL architecture that incorporates model uncertainty, cyber-attack scenarios, and network reconfiguration events
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
are recruiting PhD students to work on this exciting topic of LLM-based agentic AI, with the goal of making AI agents reliable, efficient, and collaborative. The research results are expected to become the core
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pipeline of ideas 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
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programmed in advance. If anything changes, it may fail. This project explores how to build more adaptable systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural
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PhD studentship: Teaching Intelligent Agents to See, Think and Act with Vision and Language Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI
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characterised at atomic resolution via crystal structures of PrfA–peptide complexes. Building on these findings, this PhD will develop peptide-based PrfA inhibitors as novel anti-Listeria agents. The project will
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? No Offer Description We have two exciting PhD positions at the intersection of formal software verification and Large Language Model (LLM) safety, focusing on extending state-of-the-art logic-based