41 engineering-in-image-processing-"MONASH-UNIVERSITY" PhD positions at Cranfield University
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to slow transfer times. Magdrive are developing the high-thrust SuperMagdrive propulsion system targeting 1N or higher thrust equivalent to the smallest chemical propulsion systems. Magdrive technology
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-based solutions (NbS) for water and wastewater treatment. The research will explore sustainable engineering strategies to boost their performance to deliver benefits for the environment and society. The
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opportunity in composites materials for space application research in the Composites and Advanced Materials Centre and the Centre for Defence Engineering at Cranfield university. The focus of this PhD will be
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the impacts of intermittent discharges, such as sewage overflow (SO) spills on our natural watercourses. This cutting-edge research will look at how to engineer these green technologies to maximise
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at leading international conferences and publish in top-tier journals. The successful candidate will gain advanced expertise in multi-sensor fusion, signal processing, machine learning, and positioning
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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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engineering, digital technologies, and systems thinking. The university’s strong reputation for applied research and its focus on technological innovation ensure that this project will be well-supported, with
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University provides an ideal setting for this research, offering a wealth of resources and expertise in engineering and digital technologies. The expected outcome of the project is the development of novel
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. Cranfield is an exclusively postgraduate university that is a global leader for transformational research and education in technology and management. Research Excellence Framework 2021 (REF) has recognised 88
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this research is that it should be possible to significantly improve the performance of extreme learning and assure safe and reliable maintenance operation by integrating this prior knowledge into the learning