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model, uplift service delivery, and ensure the function is positioned to respond effectively to an evolving threat landscape spanning cloud, identity, SaaS, supply chain, and AI-enabled risks. You will
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for infrastructure platforms in minerals-to-green metals transformation. It will suit a candidate interested in combining experimental materials science, advanced characterisation, and data-driven modelling to develop
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explore current techniques such as fine-tuning, model alignment, prompt engineering and Retrieval Augmented Generation (RAG) to improve reliability of generated recommendations for two cases of chronic
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of the development of connections in these biological neural networks and their spontaneous and stimulation-driven formation. These models will provide a framework for simulating and testing biological neural networks
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traditional and advanced optimization techniques, including analytical models, simulation-based approaches, and data-driven algorithms. The research also considers practical constraints such as cost, process
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social media and online platforms. The project will use natural language processing (NLP), large language models (LLMs), and network analysis to identify coordinated harassment, anti-gender equality
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strategies for countering harmful narratives, promoting healthier models of masculinity and informing policy and platform governance approaches. This PhD scholarship will be based within the Faculty of Arts