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technology increases the grid’s exposure to cyber-attacks, which can compromise measurement signals, disrupt control commands, or induce model or data-driven instability. This project aims to develop a robust multi
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programming (e.g., Python, MATLAB). Energy system modelling expertise with experience in academic research Preferred Skills: Educational background in Electrical Engineering, Computer Science, Renewable Energy
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it is driving over a damaged bridge at operational speed. Due to a lack of large, real-world datasets with ground truth labels, the application of data-driven approaches in the indirect damage
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include a research proposal aligned with one or more of the following priority areas: Research Themes Multiphysics and data-driven constitutive modelling of traumatic brain injury and its long-term impact
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Start Date: Between 1 August 2026 and 1 July 2027 This project aims to frame hypersonic aerodynamics as a grand inverse problem. By combining modern state-of-the-art AI (foundation models, physics
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loads in power system dynamics and stability as system strength continues to decline. Building on existing frameworks such as the WECC Composite Load Model (CLM), you will develop and validate data-driven
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stability as system strength continues to decline. Building on existing frameworks such as the WECC Composite Load Model (CLM), you will develop and validate data-driven methods for load identification and
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skills in remote sensing, AI, ecological modelling, and policy engagement, working across disciplines and continents. The project includes an industrial supervisor to support non-academic training and
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PhD project: Modelling Reliability and Resilience of Hydrogen Systems for Improved Safety and Sustainability Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering
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. This PhD will design methods that enable robots to achieve more robust, accurate perception and perception-driven planning for complex processes. You will investigate solutions like multi-sensing fusion (e.g