40 assistant-professor-and-human-centric-computing PhD positions at Cranfield University
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This project aims to bridge the gap between technological advancements and their integration into societal and environmental systems by shifting from a product-centric to a service-oriented approach
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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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areas. Cranfield is part of the national testbed for 6G, researching in the following areas of interest: Real-time specification of 6G telecommunication and edge computing services using Large Language
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Rolls-Royce, this project will use both experimental and computational aspects to explore the aerodynamic design space for coupled intake/fan configurations that are required to deliver more efficient
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complimentary computational studies to predict the intake aerodynamic characteristics and aid in the experiment design. This position is part of the CDT in Net Zero Aviation, which offers a modular, cohort-based
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There is an urgent need for novel freshwater quality monitoring solutions to help mitigate the risks that contaminants pose to water security, human wellbeing, and biodiversity. This funded PhD
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves
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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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learning from in-service vehicle fleets and predicting remaining useful life. Applications of artificial intelligence and computer science to battery state estimation. Reduced-authority control of hybrid