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the actuator. This involves understanding the physics of the motor, the load it is handling, and the role of the servo-controller in the system. The focus is on managing different fault scenarios efficiently
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised
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systems by developing deep learning and physics-informed deep learning models. These models will calibrate raw pressure sensor data to capacitive sensor data and incorporate flight variables to improve
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and Cyber-Physical Systems Research Assistant in Human Augmentation with AI Fixed Term Contract until 14 March 2025 or for 9 months (whichever is sooner) Full time starting salary is normally in
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manufacturing and process or material science. About the Role This is an exciting opportunity for you to contribute to a new industry project funded by Airbus on the optimisation of next-generation landing gear
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of the work. As a Research Assistant you will contribute to the research activities of the Centre for Autonomous and Cyber-physical Systems, especially concerning the specific projects described above
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to): Opportunity to speak with supervisors about the project and process; Opportunity to speak with contacts at Cranfield University and/or The National Archives regarding institutional support systems (eg
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to £40,347 per annum We welcome applications for this key research post from those with relevant knowledge and experience in advanced welding processes, additive manufacturing and process or material science
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-physical Systems at Cranfield. This exciting new role is co-developed with the Defence Science and Technology Laboratory (DSTL) and dedicated to the identified future research areas of novel human-swarm
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for Autonomous and Cyber-Physical Systems. About the Role Our reputation for leading in the field of digital systems: sensor data and signal processing for position, navigation and timing, and machine learning