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. Additionally, Life Cycle Assessment (LCA) and Environmentally Extended Multi-Regional Input-Output (EE-MRIO) models will be employed to calculate the carbon footprints of various low-carbon travel modes and
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enrichment strategies can be tailored for best conservation success. This PhD project will combine empirical fieldwork with cutting-edge spatio-temporal ecological modelling of systems dynamics to investigate
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-edge biological modelling to understand exactly how IIDs spread in nurseries. The project aims to develop improved intervention guidelines to prevent high mortality IIDs, considering what’s realistic and
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transformer in operation. On the other hand, the Total Cost of Ownership (TCO) model is widely used to measure the whole lifetime cost of the transformer. In addition to the capital cost, cost of losses
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season properties (e.g. number, intensity) for lead times ranging from one to approximately six months in the latest generation of dynamical seasonal and decadal forecast models. Seasonal forecasts
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of target species distributions by combining species presence/absence with environmental data to predict wider-scale fish distribution and identify niches Use data and models to identify: i) additional
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. The project delves into areas such as hardware-based security measures, tamper detection, and the integration of explainable AI models within embedded platforms. Situated within the esteemed IVHM Centre and
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/emissions modelling preferred but not required Creative problem-solving skills and ability to work independently *Candidates with a PhD in other disciplines may be eligible if they can demonstrate exceptional
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recovery in critical applications, including aerospace, healthcare, and industrial automation. Research Focus Areas: Predictive Analytics for Fault Detection: Develop AI models that predict potential system
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance