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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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conduct interdisciplinary research combining software engineering, artificial intelligence, IoT development, and human-computer interaction to create intelligent software systems that serve both technical
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multilayer printed circuit boards (PCBs). It draws from disciplines including electrical and electronic engineering, embedded systems, computer vision, and cybersecurity. The ability to verify hardware without
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encompassing the state of the art, evidence-based, parameter-specific production functions to estimate the relationship between transmission risk and environmental, geophysical, and demographic variables
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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-based method to approximate the CFD-revealed effects of liquid metal convection on molten pool temperature predictions. • Designing and conducting instrumented WA-DED experiments to validate the developed
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methods in the past. A piece of comprehensive computer software, Pythia with the corresponding capabilities have been developed and tested successfully in several industrial applications. The software can
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categories for a better capability of managing the uncertainty related to system complexity and data availability to achieve more accurate RUL estimations The student will have the opportunity to work with
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, computer vision or flow measurement background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience of computer coding in some form or any discipline is also
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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