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requirements: First-class or upper second-class degree (or equivalent) in Chemical/Process/Electrochemical/Mechanical/Electrical Engineering, Chemistry, or Physics, or relevant industrial experience
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integrity and durability of affected components and structures. The main challenge is assessing the transition between a relatively slow process of degradation and a rapid deterioration of structural
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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PhD Studentship – New approaches for studying the structure of high-temperature molten materials Transition: (October 2025 start) Supervisor 1: Emma Barney Supervisor 2: Oliver Alderman (ISIS
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safety? If so, this PhD opportunity is for you. The safe long-term storage of irradiated stainless steel fuel cladding is a major challenge in nuclear energy. This project will develop a novel, physics
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programme type (Research), 2025/26, Faculty of Engineering and Physical Sciences, next page select “PhD Engineering & Environment (Full time)”. In Section 2 of the application form you should insert the name
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learning (ML) techniques to gain new physical insights into fundamental questions about viscoelastic flows in both canonical configurations and porous media applications. ML techniques will be leveraged
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Research theme: Nuclear thermal-hydraulics How to apply:uom.link/pgr-apply-2425 How many positions: 1 This 3.5 year PhD is fully funded, home students and students with settled status are eligible
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be ideally suited to a person considering a PhD, or looking to gain additional research experience. The post is offered on a full time (36.25 hours per week), fixed-term contract until 30 April 2027
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Supervisory Team: Leonardo Aniello, Han Wu PhD Supervisor: Leonardo Aniello Project description: Blockchain and Federated Learning (FL) are two emerging technologies that, when combined, offer a