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to enhance sensor data accuracy and reliability in fuel tank gauging systems by developing deep learning and physics-informed deep learning models. These models will calibrate raw pressure sensor data to
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, additive 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
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of aviation and aerospace. Cranfield Aerospace’s six centres are the powerhouses of our world class research, driving technological and conceptual advances in aeronautics, propulsion engineering, cyber-physical
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aeronautics, propulsion engineering, cyber-physical systems and intelligent automation. Find out more about our work here About Aerospace . Our Values and Commitments Our shared, stated values help to define
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. Applicant will work in the Centre for Autonomous and Cyber-physical Systems at Cranfield. This exciting new role is co-developed with the Defence Science and Technology Laboratory (DSTL) and dedicated
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an Aerospace Engineering or Computer Science and knowledgeable in hardware and software for multi-sensor systems within mobile platforms or cyber-physical systems and have experience of management research using
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are the powerhouses of our world class research, driving technological and conceptual advances in aeronautics, propulsion & thermal power engineering, cyber-physical systems, robotics and intelligent automation. Our
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to add reliability, robustness, and predictability throughout the biological design process. This will be addressed with a collaborative, interdisciplinary approach with the team developing new wetware
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Management Architecture – Platform for aircraft (machine learning based algorithms could be employed to process the data provided by such approaches). You will also be responsible for managing the research