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Characterisation" "Data Science and Machine Learning in Materials" "Plastics Recycling and Circular Economy" Research theme: "Materials Characterisation" "Data Science and Machine Learning in Materials" "Plastics
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energy; thereby minimising farming’s environmental impact. AI machine learning offers a new expedient method of developing control systems for tasks that would be difficult to manage using classical
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Hydrogen is the most abundant molecule in the universe, and its interaction with surfaces plays a key role in a huge range of processes, from star formation to the safe storage of rocket fuel
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Deadline: 30 June 2025 A fully funded 3.5 year PhD position is available to work on the project titled “Scalable benchmarking for digital quantum computers based on blind testing”. This position is
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Application deadline: 01/08/2025 Research theme: Turbulence, Fluid Mechanics, Offshore Conditions, Renewable Energy, Hydrodynamics, Experiments This 3.5 year PhD is fully funded for applicants from
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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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public sources, data on the current status of ecological communities in several woodland patches across Wales, encompassing all taxa. The data will comprise species presence and distributions as
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respond over time (e.g. changing shape), controlled by the arrangement of differential materials within them. The goal of this project will be to develop responsive 4D-printed biomaterial devices for drug
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Award Summary This is a 4-year studentship. Stipend of £18,873 (stipend may be uplifted subject to confirmation) and home fees. Overview Chronic kidney disease (CKD) is one of the fastest-growing
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-printed functional devices interact with their environment, responding to stimuli (temperature, light, etc.), and “4D-printed” devices respond over time (e.g. changing shape), controlled by the arrangement