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: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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of the heart’s electrical activity, often caused by complex changes in heart tissue. Understanding and treating arrhythmias effectively remains a major challenge. Recent advances in artificial intelligence (AI
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THR demand in younger patients expected to increase fivefold by 2030, revision surgeries will also rise. To improve implant positioning, image-guided navigation is increasingly used in complex THR
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pressure to reduce both energy demand and chemical consumption. Project SandSCAPE, an Ofwat-funded programme, tackles this challenge by integrating purpose-built robots that skim slow sand filter beds while
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Organisation Job description Project and job description Our project will make use sensing technologies (hyperspectral cameras, NIR and Raman sensors), and an edge-compute AI pipeline to sort used
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of the heart’s electrical activity, often caused by complex changes in heart tissue. Understanding and treating arrhythmias effectively remains a major challenge. Recent advances in artificial intelligence (AI
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, covering all cardiac conditions. This makes them unsuitable for identifying rare or complex cases, where annotations are scarce or unreliable. Recently developed unsupervised learning methods allow
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in the SPG. We will make use of models of different complexity up to complex Earth System models, and modelling efforts for different past periods. A personalised training programme will be set up
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state-of-the-art high heat flux testing, simulating the extreme environments of fusion reactors. Harness advanced computational tools to model complex particle-material interactions and predict material