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overheating models by integrating TIR imagery with energy flux data, building physics parameters, and local weather conditions. Apply machine learning techniques for TIR and other open-source image analysis
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the design and testing of a prototype, this project will offer a robust theoretical and practical model for museums to address difficult pasts more effectively and resonantly in the digital age. This PhD
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specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision? Then check out the vacancy below and apply for a PhD position in this
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unprecedented real-time visualisation of these processes, yet systematic investigation across diverse rock types and integration with predictive models remains lacking. In this PhD study, you will be performing
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/Julia) are essential. Ideally, you will have experience with acquisition and processing of tomographic images, rock mechanics, machine learning and/or numerical modelling. Given the highly diverse nature
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new Wellcome-funded Imaging Machine learning And Genetics in Neurodevelopment (IMAGINE) lab, in the Research Department of Biomedical Computing. The post will benefit from the extensive and broad
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protocols and have affinity with medical topics. You have knowledge of CT dosimetry and radiation physics. You have good experimental skills and experience with image processing. You have some knowledge in
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DoS: Dr Michelle Harris 2nd Supervisor: Dr Andy Parsons 3rd Supervisor: Dr Katie Jones 4th Supervisor: Dr Giuliano Laudone Applications are invited for a 3.5 years PhD studentship, starting 01
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, is required. Demonstrated experience in research projects. Specific Requirements Experience in satellite image processing (Sentinel, Landsat, MODIS, etc.) LanguagesENGLISHLevelGood Additional
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The project: The focus of this project is on the novel and exciting concept of multi-rotor wind turbines; a new design paradigm for wind energy, that is attracting an increasing amount of attention