476 machine-learning-and-image-processing-"RMIT-University" PhD positions in United Kingdom
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Field
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-based structural integrity model, validated using synchrotron X-ray microtomography and phase contrast imaging, to predict the lifetime of UK’s advanced gas-cooled reactors fuel cladding in storage
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and controlling defects and lay the foundation for a thermal physics-based approach to process qualification. Additive manufacturing (AM) is a rapidly evolving technology that continues to drive
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ResTOrES project will develop, test, and demonstrate a prototype resilience assessment toolkit for offshore energy systems. The toolkit will enable the quantification of resilience in terms of appropriate
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Hydrogen is the most abundant molecule in the universe, and its interaction with surfaces plays a key role in a huge range of processes, from star formation to the safe storage of rocket fuel
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds
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we study, work, and think. Models such as ChatGPT have the potential to free individuals from the intricate and labour-intensive processes involved in writing and coding. Developing system software
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Manufacturing process for Cold Spray with Artificial Intelligence, operate the AM machine, characterise the materials with scanning electron microscopy and transmission electron microscopy with tensile testing
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difficulties), and neuropsychological sequalae such as cognitive difficulties (memory and new learning, executive function, attention, processing speed, cognitive fatigue etc.), and difficulties with regulating
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configurations. Machine learning techniques will be incorporated to dynamically adjust PST settings in response to evolving grid conditions. This multi-layered approach aims to bridge the gap between static
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microenvironment structures are associated with genomic features and clinical outcome. Danenberg E et al. Nat Genet. 2022 May;54(5):660-669. doi: 10.1038/s41588-022-01041-y Imaging mass cytometry and multiplatform