79 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof"-"Prof" positions at Cranfield University
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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learning, this research contributes to the growing field of digital healthcare, which aims to enhance clinical decision-making and improve patient outcomes. The primary focus of the project is to develop and
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This PhD project will focus on developing, evaluating, and demonstrating a framework of novel hybrid prognostics solution for selected system use case (e.g. clogging filter, linear actuator, lithium
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computational and experimental fluid dynamics in addition to product development. This project falls within the field of fluid dynamics, a discipline central to improving the efficiency of systems that involve
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conditions are often unrealistic. Solutions have been developed to introduce realistic road conditions in wind tunnel testing such as the introduction of a rolling road to reproduce ground effects (roughness
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fruitful partnership, in which the supervisor provides guidance on the nature of research and the standards expected, and the student develops as a competent researcher, fully utilising the wide range
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to identify the material degradation and coatings applications details in extreme environments. A novel techniques/method will be developed with focus on better prediction and more accurate measurement of
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expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research. The Through-life Engineering Services (TES) Centre
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This PhD is part of the new Research England-funded Future Biodetection Technologies Hub and offers an exciting opportunity to contribute the advancement of development of new sensor technologies
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expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research. The Through-life Engineering Services (TES) Centre