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modelling approach could resolve this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning
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deployment in applications. This project aims to develop a physics-based, self-learning BMS tailored specifically for Li-S batteries. The research will combine physics-driven models with machine-learning
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velocity and total pressure. The project will investigate how machine learning and data-driven methods can be used to: Develop surrogate models that predict distortion metrics from sparse sensor
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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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decarbonisation of aviation sector: I am keen to work with British nationals to develop ideas to secure a PhD studentship. Cranfield is part of several networks to enable this. Just get in touch
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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 the
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£36,487 in London. This PhD examines whether low-carbon investment reduces regional gaps in employment, incomes and energy affordability. Applicants could focus on renewable energy, electricity
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This fully funded PhD (open to any nationality), sponsored by the European Union Horizon Europe programme, offers an exciting opportunity to develop next-generation digital twins for offshore wind
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This fully funded PhD (open to applicants of any nationality), sponsored by the European Union Horizon Europe programme, offers an exciting opportunity to develop next-generation digital twin
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diagnosis and prognosis technologies, and, consequently, improve maintenance decision making. Currently, machine learning exists as the most promising technologies of big data analytics in industrial