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Fully Funded PhD Studentship (UK Students Only) Real-Time Sub-THz Electromagnetic Sensing and Machine Learning for Dynamic Particulate Characterization University of Birmingham with support from
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Advances in manufacturing science have resulted in unprecedented research and development in the design of ‘micro-swimmers’: microscopic entities that navigate fluid environments by converting some
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will design and validate a cost-effective, synchronised multi-node sensing system for simultaneous time-domain measurements of voltages, currents, electric fields and magnetic fields, supported by
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Priority will be given to the following designated employment equity groups: Indigenous Peoples* (First Nations, Inuit and Métis), persons with disabilities and racialized persons*. * The Employment
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motivation Testing whether the system performs equitably across cultural and language groups Training spans intervention design, trial methodology, human-computer interaction, and applied machine learning
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candidate for a full-time (100%) PhD position for 3 years. You will join the research group Power Electronics and Electrical Machines (PEM) at IEL, where we foster an open, inclusive, and collaborative
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Auditory SCEnes in Humans and Machines), an ERC Synergy project conducted in collaboration with Dr. Bruno Giordano (CNRS, Marseille). NASCE brings together cognitive neuroscience, advanced neuroimaging
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layer and its techniques – the candidate will design, implement and evaluate an AI-driven MAC-control framework that self‑heals in integrated terrestrial-NTN (LEO, HAPS, UAV) 6G networks. The work will be
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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: Design, implement and characterize innovative sensing systems based on different sensing principles such as ultrasonic, optical and chemical sensors. Investigate sensor behavior under varying environmental