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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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research group, which leads pioneering work in multi-sensor navigation, signal processing, and system integrity for aerospace, defence, and autonomous systems. The research will deliver a comprehensive
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/learning based techniques in the areas of robotics, or autonomous systems, • interested in autonomous systems and signal processing, • Keen to work with equipment and embedded
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costs. Condition monitoring (CM) of rolling element bearings, hereafter called bearings, has been the main point of attention for many decades in the industry for maintenance. This is because bearings
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-periodic structures, we can precisely control the interaction of radiation with matter, potentially achieving unprecedented timing resolution (sub-70ps) and significantly enhancing signal detection. This PhD
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the areas of robotics, or autonomous systems, interested in autonomous systems and signal processing. Keen to work with equipment and embedded platforms. Funding To be eligible for this funding, applicants
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performance simulation capabilities for gas turbine engines developed at Cranfield University as the starting point. Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power
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electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering. Funding This is a self-funded PhD. Find out more about fees
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. Simulations are suitable to characterise processes in healthy and diseased individuals including stroke patients. Machine learning methods might be considered to accelerate simulations. The project provides a
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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