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Two fully-funded 3-year PhD studentships are available in Neuromorphic and Bio-inspired computing at the interface between control engineering, electrical engineering, computational neuroscience
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, advanced gel polymer electrolytes (GPEs) are needed to boost energy density and reliability. This PhD project offers a unique opportunity to develop cutting-edge GPEs that combine the safety of solid-state
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technological advances that support the global transition toward net-zero emissions and sustainable aerospace engineering. Motivation The reliability of electric propulsion systems is pivotal for next-generation
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emissions and sustainable aerospace engineering. Motivation The reliability of electric propulsion systems is pivotal for next-generation energy and aerospace solutions. In particular, surface-mounted
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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transmission is a foundational technology for modern power systems, efficiently delivering electricity over long distances and enabling the integration of remote renewable energy sources. As renewable
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on the reliability of the transformers. Hence this research aims to develop a multi-objective optimisation method to incorporate carbon footprint, total cost of ownership and the transformer reliability in selecting
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. Experimental validation will be used to refine simulation accuracy and ultimately establish a reliable toolset for testing and developing fusion-relevant materials. Cranfield University is internationally
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for the next generation of thermal barrier coatings (TBCs) for aero-engines. The PhD Project Advanced TBCs are used in critical aeroengine components (e.g., Ni superalloy turbine blades) to ensure a reliable and
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. While autonomy is becoming more integrated into modern mobility, the reliability of Position, Navigation and Timing (PNT) systems—especially in environments where GNSS signals are denied or degraded