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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
for automated, data-driven diagnostics, integrating AI with high-resolution imaging and sensing offers a transformative solution. AI models can learn to recognize subtle damage patterns, enabling faster, more
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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. The partnership project combines digital agriculture, crop modelling and molecular breeding to improve the resilience and sustainability of the East African tea crop. You will have the opportunity to visit data
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production-grade system that integrates Vision Transformers for visual deepfakes, advanced Natural Language Processing (NLP) models for phishing detection, and a dedicated Explainable AI (XAI) layer
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modelling, artificial intelligence, or marine operations. The project aims to develop a human-factor-informed simulated digital twin framework to assess technician welfare during offshore wind farm
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digital agriculture, crop modelling and molecular breeding to improve the resilience and sustainability of the East African tea crop. You will have the opportunity to visit data collection sites in the tea
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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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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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modelling tools to understand and tailor the physical and chemical interactions at the interfaces within metascintillators. Cranfield University’s Centre for Materials is internationally recognised