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Multiple self-funded PhD positions are available in Modelling and Simulation (M&S). The project will aim to mature software repositories describing the biomechanics of the human brain. The M&S tools
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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
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real-time fault detection and predictive maintenance strategies. 3. Validation of AI models with real-world SCADA data, ensuring industry relevance. 4. A digital twin framework for safe, simulation-based
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the development of a low fidelity pump model that accounts for unstable and multi-phase flow behaviour through high fidelity simulations. This will be used to develop an integrated fuel system model that will
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targets the development of advanced coatings to prevent cell-to-cell propagation during runaway events. It combines experimental studies, numerical modelling, and real-world burner rig testing, culminating
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fabrication laboratories. Hands-on experience in surface engineering and scintillator detector testing. Training in modelling and simulation of radiation–matter interactions. Opportunities to present research
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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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the molten pool. However, these models are computationally intensive and impractical for widespread simulations of large-scale part deposition. This project aims to develop a novel FEA-based approach
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limitations in both measurement and modelling techniques. Current in-process measurement methods are restricted to surface-only monitoring devices (e.g., cameras and pyrometers), which fail to capture
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to High-Fidelity Simulations – The project will use OpenFAST, FAST.Farm, and Digital Twin simulations for AI model validation. The student will have the opportunity to join a vibrant community and team