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will use advanced unsteady computational fluid dynamic methods for the analysis of coupled intake/fan configurations in crosswind and high-incidence conditions. The research will adopt these methods
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simulating fluid networks and dynamic phenomena for assessing different solutions is a necessity The overall aim of this project is to improve the confidence in fuel system design process for ultra-efficient
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from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This network brings together both research students and staff
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experience in numerical fluid dynamics is beneficial but not essential; determination, curiosity, and a willingness to learn are key attributes we value. Applicants with alternative qualifications, industry
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. This project aims to dive into the dynamics of attack methodologies (e.g., Membership Inference, Property Inference) and defensive mechanisms (e.g., Differential Privacy, Machine Unlearning) within FL
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field, as well as being part of our strong and dynamic research centre at Cranfield University. Cranfield is an exclusively postgraduate university that is a global leader for transformational research
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The research in this doctoral opportunity will investigate the relationship between material elastic and thermal properties by using high resolution digital imaging under dynamic loads. Digital
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. The student will have the opportunity to work with experts in the data analytics and condition monitoring field, as well as being part of our strong and dynamic research centre at Cranfield University