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behaviour. In addition, you can use cost-benefit models to explore how an AMOC tipping point may influence financially optimal strategies, and/or agent-based models to explore how an AMOC tipping point will
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of the PhD topic (subproject A7- Reinforcement learning for mode choice decisions): This PhD project will develop and implement a Deep Reinforcement Learning (DRL) model for dynamic mode choice within
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in AI: Generative Diffusion & 3D/4D Scene Synthesis: Re-design diffusion and NeRF-style models so multiple agents jointly reconstruct a scene. Semantic-Aware Compression & Network Information Theory
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cybersecurity allowing thus to validate and receive feedback from on-the-field cybersecurity practitioners. As generative AI (GenAI) platforms and large language models (LLMs) are increasingly integrated
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on these comparisons, you will create agent-based models (ABMs) that define interaction rules based on observed similarities and differences in events [4], with a focus on the specific role of individual differences
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. This exciting project is funded by a Industry PhD Program. Flinders University and Bookbot.com, are partners in the program. The student will be based at Flinders University for 4 days a week. The candidate will
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: Coordination Layer: Formulate passivity-based conditions that guarantee agents—modelled as general nonlinear systems—synchronize their outputs or follow desired collective patterns purely through local
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powerful AI companies, in democratic security, and analysis of the development of new forms of agentic and adversarial AI that could undermine democracy. The candidate will be based in Lancaster University’s
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with reducing and oxidising gas-phase species (e.g. laser-based imaging diagnostics, setup of model reactors, modelling of underlying reactions, multi-scale simulation of reactive fluids, computational
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findings at meetings and/ or conferences. Lead the definition and documentation of requirements, architecture and design of secure, scalable, asynchronous, agentic systems, based on knowledge of principles