8 neuroimaging-machine-learning-engineer PhD positions at The University of Manchester
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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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motivated candidate with an interest in building quantum technology and learning a wide range of skills in optical systems, precision measurements, electronic control and feedback systems, vacuum systems
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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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training in materials engineering, corrosion, and materials selection. You will become a specialist in the field of corrosion and hydrogen, opening up prospect for top-class employment & cutting edge job
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(contributing approximately 50%), advancements in aircraft technology (30%), and operational improvements (20%) – together supporting the industry's 2050 carbon-neutral growth objectives. Broadly, this project
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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