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model development, robustness, and long-term reliability. What you can expect Modelling. Apply probability theory, statistical analysis, and machine learning techniques to build robust models and generate
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
engineers detect faults earlier, track system degradation, and make better-informed maintenance decisions. But how can we turn this complex information into something reliable, explainable, and actionable
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thus including sensing systems, tool condition features selection, algorithms for automated signal preprocessing, feature extraction and decision making based on ML and AI. An integral part of
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large dataset analysis, improving decision-making processes for awarding grants to firms and scientists. The PhD project could aim at the following issues: Improved Funding Decisions: How can we make
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decisive clinical and public health decision making. You’ll be using metagenomic techniques gaining practical experience of their laboratory use, but much of this project will be analytical applying
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approximately six months. The independent body that selects the award winners is comprised of approximately 22 academics of all disciplines; it meets twice a year and makes its decision based on the independent
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language understanding, and more. Your work will directly influence our trading strategies and decision-making processes. This is a unique opportunity to work at the intersection of cutting-edge research and real-world
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of resources, materials, and activities. This improved transparency facilitates decision-making and collaboration across projects. The position is funded by the research project “TWinYards - Scaling up
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
system health monitoring, and more efficient maintenance planning. Digital twins offer a powerful foundation but must evolve beyond simulation to truly support engineering decisions. This PhD will develop
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engines. The variable rotation speeds, complex loading and operating conditions cause significant blade vibrations. These vibrations, if not properly controlled and reduced, can lead to premature blade