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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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, information loss is inevitable, thus it is natural to drop “unimportant” data patterns in a visualisation result. In practice, the desired data pattern and structure to preserve in a visualisation result can
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Innovation Future Leaders Fellowship. The funding is for home and overseas students. Power systems are going through unprecedented changes, driven by the need for decarbonisation but also due to other
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, training, and collaboration Preferably a strong background in aircraft design and propulsion systems Preferably Proficient in programming (MATLAB preferred; Python is also acceptable) Prior experience with
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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