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sensing technology. You will refine and optimise a bespoke characterisation system, fabricate optical fibre sensors and evaluate their performance. You will also apply digital signal processing techniques
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Strong skills in simulation methodologies Excellent communication and interpersonal skills Desirable Criteria: Familiarity with machine learning algorithms and artificial intelligence as applied
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learning algorithms. Collaborating with industry partners to understand operational requirements and developing AI pipelines for analysing visual and sensor data collected during inspection processes
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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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. The role would involve optimizing an artificial touch sensor for use in detecting defects during composite layup, as well as developing algorithms and visualization tools to demonstrate its performance
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variations and sensors malfunctions. • Robust and efficient CF control with Level 5 EV automation tracking accuracy under harsh operating conditions, and automated identification algorithms for self
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, information sharing, reporting and robot navigation. Develop sensor data fusion algorithms that are an essential element of the joint robot mapping tasks in the presence of data origin uncertainties. Knowledge
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the development, implementation, and testing of signal processing and imaging algorithms for high-frequency ultrasound structural and functional imaging. Support experimental setup, data collection, phantom
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-making, information sharing, reporting and robot navigation. Develop sensor data fusion algorithms that are an essential element of the joint robot mapping tasks in the presence of data origin
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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