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Applications are invited for an employed Doctoral Candidate to be funded by the Marie-Skłodowska-Curie Learning Network for Decentralized critical Infrastructure Asset Monitoring and coNDition
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the Marie-Skłodowska-Curie Learning Network for Decentralized critical Infrastructure Asset Monitoring and coNDition assessment (DIAMOND), a stimulating, high-level European Doctoral programme including 16
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prescriptive maintenance system for Genie’s lifting equipment. The project focuses on connected, partially connected, and non-connected machines, transforming telematics, onboard sensor data, and historical
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’–mechanical networks built from many sensors and actuators that locally communicate with one another to achieve collective functionality. These active networks could enable next-generation bioinspired robots
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knowledge of artificial sensors and neural networks. You will have access to state-of-the-art facilities at Bristol Robotics Laboratory, the largest centre for multidisciplinary robotics research in the UK
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complementary areas above is welcomed. We particularly welcome applicants whose work has bridged from adjacent backgrounds — materials, devices, sensors, photonics, RF, power electronics (GaN/SiC), or board-level
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applicants whose work has bridged from adjacent backgrounds — computer architecture, embedded systems, FPGA-based research, accelerator or hardware-software co-design, low-power or sensor or quantum-hardware
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per year, subject to annual increases. About the Project (Background & Methodology) Autonomous systems such as drone fleets, mobile robots, and sensor networks increasingly use federated learning (FL
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: offshore wind turbines, wave tank experiments, fluid-structure interactions, sensors for offshore structural health monitoring, software development, machine learning and advanced AI modelling, and previous
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in analogue and mixed-signal circuit design, including analogue VLSI design, sensor interfacing, low-power mixed-signal systems, and related integrated semiconductor technologies. We seek a circuit