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, combustion, and process optimisation. The project is focussed on the development of novel interface capturing Computational Fluid Dynamics methods for simulating boiling in Nuclear Thermal Hydraulics
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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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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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should have a strong mathematical background, particularly in dynamical systems theory, and a keen interest in network science, and scientific computation. The student will gain invaluable experience
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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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University Technology Centre (UTC) in Manufacturing and On-Wing Technology, The University of Nottingham. Applicants are invited to undertake a 3-year PhD program in partnership with the UK Atomic Energy
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dynamic environments, including narrow spaces and interactions with unfamiliar objects. This project aligns with Rolls-Royce’s technical needs for developing soft robotic solutions to enable in-situ/on-wing
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integrates dynamic “smart” materials into 3D-printed structures, opens new frontiers in both bioelectronics and solar energy harvesting. Our goal is to create adaptive electrode architectures. These advanced
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covers tuition fees, a stipend, and RTSG (research training and support grant). Alongside the scientific PhD training, the programme will provide a wide range of training opportunities. DTP Standard
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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which