43 high-performance-quantum-computing-"https:"-"https:"-"https:" PhD positions at Cranfield University
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This PhD project aims to address one of the key challenges in the manufacturing industry, the increase in productivity by utilizing the equipment with its optimum performance and without any
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Develop practical, industry-transforming technology in this hands-on PhD program focused on immediate industrial applications. This exclusive opportunity places you directly at the interface between
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detection of chemical and microbial contaminants in rivers. The studentship is funded by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme, which is supporting new research
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
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. The studentship is funded by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme, which is supporting new research on human-environment interactions in freshwater ecosystems. There is an
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Verification Tools: Develop AI algorithms that automate the verification process, ensuring systems meet required safety and performance standards. Health Monitoring Algorithms: Implement AI-based monitoring
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sensors to deliver resilient, high-accuracy positioning. The project sits at the intersection of navigation, AI-enhanced signal and data analysis, and wireless communication systems, with applications in
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temperatures in modern Gas Turbines. During the operation of gas turbines, such high temperatures are coupled with the impurities or ash compounds like Sulphur, halides, sodium and vanadium. In certain cases
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covers fees and stipend for a home (UK) student with funding provided by the Leverhulme Trust through the Connected Waters Leverhulme Doctoral Programme. Options exist for PhD and Master + PhD routes
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves