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particles that may trigger early ignition. These phenomena can compromise engine safety, performance, and durability. In this project, you will explore how different oil formulations and engine parameters
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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if this is the case. As this is the methodology used by government to assess and compare the energy and environmental performance of dwellings, the current rating disincentivises developers from specifying
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This PhD project will focus on developing, evaluating, and demonstrating a framework of novel hybrid prognostics solution for selected system use case (e.g. clogging filter, linear actuator, lithium
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wealth inequality, and how their career paths, values, and social networks maintain the status quo. As a PhD student on this programme, you’ll play a key role in generating new insights that could help
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to rare disease trials. This PhD studentship is part of LifeArc ARDT, a UK-wide £12m partnership between Newcastle, Birmingham, and Belfast to accelerate rare disease trials. Students will receive training
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suggest hypotheses for therapeutic targeting. This PhD studentship is part of the LifeArc ARDT, a UK-wide £12m partnership between Newcastle, Birmingham, and Belfast to accelerate rare disease trials
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AI approaches have recently been used to detect Alzheimer’s disease from CFPs among those with established disease (in case-control studies), the use of such approaches to predict disease (i.e., in
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. For eligible students the studentship will cover Home or International tuition fees plus an annual tax-free stipend of at least £19,237 for 3.5 years full-time, or pro rata for part-time study. The student
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hydrological outcomes which may feed back to the cryospheric system. So far ecological, hydrological, and cryospheric work has been conducted separately. To address this gap, our project integrates