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combination of overseas field work (Europe and other locations), image based and laboratory work to characterise soil properties to address the questions above. The imaging work will be a combination of GIS
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new family of solid-state Additive Manufacturing technologies, such as Cold spray. The nature of the process utilising low heat input and severe plastic deformation, produces ultra-refined
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with transferable expertise applicable across AI-driven domains. Application Process To apply, please send a CV, cover letter, and transcripts to Dr Christopher Wood (christopher.wood@nottingham.ac.uk
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to produce anti-counterfeit markings, dye-free colour images, humidity and chemical sensors, anti-glare coatings and optical filters. This project will develop additive manufacturing of devices with actively
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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explore or optimise the flexible structures and manufacturing process of Litz wires. This studentship offers the opportunity for the PhD student to lead the development of innovative simulation tools
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supercritical water systems to generate samples that will help optimise a process that will then be scaled into pilot and large scale pilot systems with partners in the consortium. Aim This project will focus
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desirable but learning can be completed during the PhD. Excellent communication and interpersonal skills to facilitate collaboration within interdisciplinary research teams. Application Process: To apply
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rely on unsustainable materials and on carbon-intensive manufacturing processes. This is posing major environmental and ethical challenges. The project will motivate the PhD student to develop next
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://nottingham.ac.uk/ComputerScience/Studywithus/Postgraduateresearch/NottinghamDTCinAI.aspx Entry Requirements: 2:1 Bachelor or Masters degree or international equivalent in a related discipline Application Process