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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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(School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025 Eligibility: Home students only | Minimum 2:1 in a relevant discipline Stipend: Home students only
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supervisors spans five departments at University of Nottingham including Architecture and Built Environment, Electrical and Electronic Engineering, Mathematics, Physics and Social Sciences. The PhD programme
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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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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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considering various elements in the process. The integration of computer vision techniques in this project will also enhance the value of this work. The students will not only gain an experience and insight
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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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cohort to benefit from peer-to-peer learning and transferable skills development. For full information about the programme, the research projects available and how to apply, please visit: http
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At the Mixed Reality Laboratory, School of Computer Science, University of Nottingham Closing date: 28th March 2025, interviews will take place in April and May Department: Computer