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-periodic structures, we can precisely control the interaction of radiation with matter, potentially achieving unprecedented timing resolution (sub-70ps) and significantly enhancing signal detection. This PhD
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costs. Condition monitoring (CM) of rolling element bearings, hereafter called bearings, has been the main point of attention for many decades in the industry for maintenance. This is because bearings
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This PhD project aims to reduce—by approximately an order of magnitude—the time and computational effort required to evaluate point-defect energetics in technologically important mixed-anion
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adaptive signal processing whose combined performance and resilience can easily exceed that of the sum of their parts. However, fundamental and significant questions to provide their practical feasibility
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at the interface between stochastic modelling, signal processing and data science. Ultimately, the project will develop key indices that can be used to assess the health of the soil ecosystem. Such indices
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the areas of robotics, or autonomous systems, interested in autonomous systems and signal processing. Keen to work with equipment and embedded platforms. Funding To be eligible for this funding, applicants
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performance simulation capabilities for gas turbine engines developed at Cranfield University as the starting point. Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power
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no generalised agreement about the qualities that determine whether the model is good or not. The focus of this project is whether the model is good enough for the point in a project’s lifecycle and not whether
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 2 months ago
of an accurate and generalisable density Equation of State model (EoS). This is especially challenging near the critical point and the Widom line, where there are large gradients in fluid properties. This project
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of organisation-wide processes such as strategy formulation and human resources with R&D; The relationship between organisation-level activities and performance, and national and regional innovation systems