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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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remuneration package (including 39 days off a year and generous pension schemes). Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your
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. Wand, Simon Gibbon, Mark Irwin, Flor Siperstein, Stuart Lyon, The effect of cross-linker structure on interfacial interactions, polymer dynamics and network composition in an epoxy-amine resin, Applied
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define observable events based on expert knowledge and available evidence. Development of a post-race analysis structure, process and data ‘toolkit’ that can build on historical understanding of race
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researcher with expertise in communication, project management, and leadership. You will build a robust national and international network and acquire advanced knowledge essential for implementing critical
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methods in the past. A piece of comprehensive computer software, Pythia with the corresponding capabilities have been developed and tested successfully in several industrial applications. The software can
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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microscopy tools such as SEM/EDX, FIB and TEM. Also use dimensional metrology for metal loss evaluation. Thermodynamics calculations using FactSage software will also be used. The candidate will be based
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, biologists, and engineers. You will also have the opportunity to present your research at international conferences, expanding your network and gaining valuable experience in scientific communication
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on defining the initial separated fuel length scales. Fundamental to the definition of primary breakup correlations is the Weber number, which describes the ratio between air momentum and fuel surface tension