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are poised to re-define our future mobility. However, full autonomy is not possible without all-weather perception for which Radar sensing/imaging is essential. This project focuses on developing algorithms
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compared to the current state-of-the-art. The project will align the in-house algorithm-to-hardware development of the Micro-Systems Research Group at Newcastle University with next-generation Field
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difficult to deploy outside large data centres. This PhD project focuses on developing resource-efficient computer vision methods that maintain strong performance while dramatically reducing computation
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of the following objectives: Design and development of long dwell-time, distributed signal processing algorithms for improved target detection Design and development of signal processing techniques for enhanced
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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instrumentation of the structure, whilst effective, can be logistically expensive to implement for the entire network. To address these challenges, the project aims to develop a novel, population-based indirect
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promising targets for antiviral drug development. While the COVID-19 pandemic highlighted the threat of RNA viruses, large DNA viruses such as African Swine Fever Virus (ASFV) remain underexplored despite
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project aims to develop state-of-the-art computational methods to optimise the quality of doubly curved shell structures manufactured from recycled, short-fibre composites. A particular novelty of the
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modelling becomes crucial for developing effective mitigation and adaptation strategies for marine infrastructure. Within the Institute of Infrastructure and Environment, we maintain a track record in the
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person. Aims: The project aims to develop and evaluate AI methods for medical image analysis to detect diabetic retinopathy, glaucoma, cataract and age-related macular degeneration (AMD). As