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with engineering, physics, mathematics, acoustics, fluids, electronics or instrumentation background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience
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, multidisciplinary PhD research projects across areas such as: Zero Emission Technologies. Ultra Efficient Aircraft, Propulsion, Aerodynamics, Structures and Systems. Aerospace Materials, Manufacturing, and Life Cycle
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University. Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power Engineering, Cranfield University, in the area of gas turbine performance, diagnostics and prognostics
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aircraft. While working on this exciting research project, you will be provided with: A fully funded 4 year full-time PhD - £24,000 tax-free stipend per year. Attendance/presentations to international and
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, embrittlement, and cracks. This will be achieved by integrating ultrasonic arrays with inverse modelling methods to interpret historical data. Additionally, the project will explore the failure mechanisms
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unbounded variable and instance sets. In addition, novel approaches such as Physics Informed/Guided Learning allows the learning models to capture the underlying physics/patterns and to generate physically
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of big data might not be possible to be captured by traditional modelling approaches. This implies that mathematical modelling of such data is infeasible. The data-driven modelling approach could resolve