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-Based Modelling ✔ Data Science & Advanced Analytics with real-world SCADA data ✔ Renewable Energy Systems & Wind Turbine Engineering ✔ Industry Engagement & Research Commercialization ✔ Scientific Writing
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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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Tomography (ToF-PET) offers vital functional and molecular insights for improved cancer staging, its current capabilities are often limited by the timing resolution and sensitivity of existing detector
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(ToF-PET) provides critical functional and molecular insights to improve cancer staging but is currently limited by detector timing resolution and sensitivity. Metascintillators, an emerging family of
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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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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
placement with Rolls-Royce. The research focuses on AI-driven digital twins, using large language models and knowledge graphs for predictive maintenance in aerospace systems. Aerospace systems generate vast
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flow visualisation and measurement techniques to study droplet impact under icing conditions to improve icing codes that aid in design and development of ice detection and mitigation system
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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testing and computational modelling. You'll become part of a diverse, multidisciplinary team that prioritises equity, diversity, and inclusion, gaining specialist expertise in hydrogen-material interactions
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maintenance. However, current technologies are relatively slow and not capable enough to provide quick performance, diagnostic and prognostic predictions for real time applications. With the rapid development