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, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Strong background/skills on machine learning, mathematics, probabilistic
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filled. This fully funded PhD explores AI-native and sensing-aware wireless systems where communications and sensing are co-designed end-to-end. You will unify modern machine learning, statistical signal
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. Fe, S) on CNT purity and structure. Evaluate CNTs as conductive additives in standard Li-ion battery electrodes. Apply AI/machine learning to optimise experimental design and growth parameters
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Engineering, Computer Science or related disciplines. Experience in autonomous system, manufacturing/robotics and machine vision development will be an advantage. To apply please contact the supervisor, Dr Kun
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aesthetic appeal. Since the first synthesis of a catenane in 1960, mechanical bonds have been used in a variety of contexts and their dynamic properties have been exploited to build molecular machines and new
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Gamesa Renewable Energy R&D team and also undertake an industry placement as part of the PhD programme. To apply, please contact the main supervisor, Dr Chen - lujia.chen@manchester.ac.uk . Please include
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to conduct impactful research and pursue excellence High levels of enthusiasm, passion, and self-motivation for sustainable aviation Intellectual curiosity and a willingness to learn through literature review