42 postdoc-in-distributed-systems-and-controls-"Multiple" PhD positions at Cranfield University
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The Structural Battery Company, a high-tech manufacturer of EV batteries. Building on Cranfield’s previous APC-funded CERABEV successes using epoxy-based systems with intumescent ceramic phases, this project
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and kinematic models with machine-learning-based channel state information (CSI) prediction to enable robust, low-latency connectivity across multi-layer NTN systems. This PhD project sits
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This self-funded PhD opportunity explores assured multi-sensor localisation in 6G terrestrial and non-terrestrial networks (TN–NTN), combining GNSS positioning, inertial systems, and vision-based
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Fully funded Ph.D. opportunity in Aerospace AI. Sponsored by EPSRC and BAE Systems covering tuition, fees and a bursary of up to £19,569 (tax free) + £7,500 industrial top-up. Combinatory Artificial
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This self-funded PhD opportunity sits at the intersection of several research domains: multi-modal positioning, navigation and timing (PNT) systems, AI-enhanced data analytics and signal processing
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significant weight savings, and improve the overall efficiency of the Hydrogen system, and at the end, of the aircraft. Nevertheless, to deliver those expected benefits, it is absolutely necessary to understand
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This project is sponsored by EPSRC, Cranfield University and a consortium led by ETN global. ESPRC will provide stipend (£22,000 per annum) and cover UK fees. The consortium will provide supervision
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Nuclear fusion offers the prospect of clean, abundant, and safe energy that could transform global energy systems. Achieving this goal depends on materials that can endure extreme environments
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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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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