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for constraining the spin of the compact object being lensed which will involve both theoretical and computational modelling. If you wish to discuss any details of the project informally, please contact: Prof
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Bhutan (covering 2013–present, at resolutions from 15-minute to daily). Objectives for this project are flexible, but include: Harmonising timestamps, units, and metadata across the seven national datasets
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project
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co-supervised by both academic and industry experts, gaining valuable skills at the interface of hydrogeology, environmental engineering, and computational modeling. Research Objectives (1
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process is poorly recorded and needs improvement. Aims and Objectives In collaboration with the Health Innovation Partnership, a modelling pipeline will be devised to cope with the challenges of data
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turbulence due to varying bathymetry, bed roughness, and due to boundary forcing due to free surface changes or fixed lateral channel boundary. The research objectives include designing an experimental
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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behaviour, improve body composition and modulate stress. However, people often find starting an exercise programme a daunting experience and there are many barriers that prevent women from getting lifestyle
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compliance and operational integrity. The application of AI in these areas enhances the ability to predict system behaviours, detect anomalies, and streamline certification workflows. AI-driven tools can
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of synthetic load profiles for domestic heat demand delivered via ASHPs and heat networks. Objectives: • To complete an evaluation of existing heat demand, based on available data sets; • To analyse