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This is a self-funded opportunity relying on Computational Fluid Dynamics (CFD) and wind tunnel testing to further the design of porous airfoils with superior aerodynamic efficiency. Building
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, embedded intelligence, and adaptive cyber-physical systems that operate safely under uncertainty and dynamic conditions. This PhD at Cranfield University explores the development of resilient, AI-enabled
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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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Cranfield University and Magdrive, offer a fully funded PhD position under the umbrella of the R2T2 consortium to study the optimisation of their thruster for a kick stage. R2T2 is a UKSA-funded
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Computing Strategies: Develop algorithms that dynamically adjust computing resources to minimize energy usage without compromising performance. Thermal Management Techniques: Design systems that effectively
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NbS including treatment wetlands (TWs) and sustainable drainage systems (SuDs) at water recycling centres and within individual surface water catchment areas, respectively. These systems offer
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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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increasingly important. The aim of the project is to explore the collaborative dynamics of agents within eCPS, with a specific focus on aligning their behaviours towards achieving sustainability goals. Cranfield
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, such as environmental, ecological or civil engineering, environmental science, hydrology, ecology, water resources management, and geography. A full-UK driving license is essential. The ideal candidate
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experts in the prognostics and condition monitoring field, as well as being part of our strong and dynamic research centre at Cranfield University. About the host University/Centre Cranfield is an