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uncertainties make planning and decision-making more complex and difficult to optimise using conventional approaches. This project aims to develop advanced modelling and simulation frameworks to support decision
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, radiologists interpret scans such as CT, MRI, and X-ray together with textual information, including patient history, laboratory findings, and prior reports. Although recent Vision–Language Models (VLMs) can
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PhD Studentship in Computational Modelling and Optimisation of Plasma Systems We invite applications for a fully funded PhD studentship focused on the computational modelling and optimisation
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by understanding how cancer risk prediction models are influenced by missing and incomplete symptom data recorded in electronic health records (EHRs) and developing methods to address any issues
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algorithms that combine Reinforcement Learning techniques like Partially Observable Markov Decision Processes (POMDPs) with cognitive inference modules capable of modelling human beliefs, intentions, and goals
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harvesting recent breakthroughs in Machine Learning (ML) and analytical modelling. Specifically, this project seeks to quantify key performance metrics and create powerful adaptive ML-driven management methods
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its interactions with different midbrain regions. The successful candidate will use a variety of systems neuroscience techniques in rodent models to interrogate neural circuits underlying affective
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three coupled components. First, a physics-informed graph surrogate model will emulate network hydraulics at scale, representing pipes and assets as a graph and predicting flows, depths, surcharge
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relevant discipline. Experience with modelling or simulation tools (e.g., MATLAB/Simulink, PSCAD, PowerFactory, or Python) is desirable.
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, populations, and types of amenities remains largely unexamined. Why 15, rather than 10, 20, or 30 minutes? The assumption that the health and wellbeing benefits of this model will be evenly distributed is