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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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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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(agent-based modeling, differential equations) or machine learning tools. Good programming skills in one of the following programming languages: R, Python, MATLAB, or similar; Excellent English language
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vulnerabilities. Frontier models show superior performance when combined with a focused knowledge base and multi-agent architectures. However, in most cases human involvement is still required, and fully autonomous
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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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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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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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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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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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We are seeking one outstanding candidate for a PhD scholarship to work on a project entitled: Human-Centred AI EdTech: Promoting Reading Engagement and Emotional Well-being in Children