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Field
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student will take advantage of state-of-the-art soft polymer fabrication (3D/4D printing) and characterisation (i.e. electro-mechanical multi-axial testing rigs) equipment and the latest computational
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of MILD combustion. The post holder will be located in Central Cambridge, Cambridgeshire, UK. The key responsibilities and duties are to perform experiments with liquid-fuelled and hydrogen flames, employ
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A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on experimental investigations of MILD combustion. The post holder will be located in Central
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for constraining the spin of the compact object being lensed which will involve both theoretical and computational modelling. If you wish to discuss any details of the project informally, please contact: Prof
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aligned subjects The Project start dates: October 2025 – Home students only January 2026 – Home and International students Supervisors: Aligned programme of study: PhD in Chemical Engineering Mode of study
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, this is only available to those eligible for UK fees. All applications should be made online via the above ‘Apply’ button. Under Campus, please select ‘Loughborough’ and select Programme ‘Chemistry’ Please
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the PhD in Engineering programme. Make sure to reference the supervisor's name (Dr Farzad Hayati) in your application. Informal enquiries are welcome and should be directed to Dr Farzad Hayati at f.hayati
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boundaries. This fully funded PhD scholarship is suitable for students with a background in Engineering Design, Smart Manufacturing, Aerospace Engineering, Mechanics, Computer Science, Mathematics, Life Cycle
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Can We Teach AI to Outsmart Humans in the Werewolf Game—Without Changing the AI Itself? Large Language Models (LLMs) have dazzled us with their ability to converse, code, and create—but they still struggle in areas where humans excel: reasoning about other players, forming alliances, and making...
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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had