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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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This is a fully funded PhD (fees and bursary) in experimental icing research. Fundamental understanding of droplet impact dynamics is integral to icing. The overall aim of this PhD is to use optical
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or in an academic role. We will help you develop into a dynamic, confident and highly competent researcher with wider transferable skills (communication, project management and leadership) with
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. By integrating artificial intelligence (AI), multi-sensor fusion, and cognitive systems, the research will pioneer robust navigation architectures. These improvements are key to making future transport
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research projects across areas such as: Zero Emission Technologies. Ultra Efficient Aircraft, Propulsion, Aerodynamics, Structures and Systems. Aerospace Materials, Manufacturing, and Life Cycle Analysis
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. This provides a unique capability to assist researchers and engineers in gas turbine performance and health monitoring in gas turbine and power generation industry. The history of gas turbine performance
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developing novel composite materials with superior ballistic and hyper-velocity impact protection. The PhD research will help improve the reliability and longevity of space satellites. Composite materials have
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. Furthermore, the research will help develop the necessary skills and expertise required to tackle the product development, testing and certification associated with achieving Net Zero aviation. Collaborating
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more research is required to establish the inter-dependencies between these properties with the help of high resolution images. In this research, different sets of composites material will be dynamically
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attracted intense interest from both academia and industry recently for its attempt to extract more useful information and knowledge from Big Data. Big Data analytics will help to develop more advance