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circuits and electronics integration. It is desirable that the candidates have sound knowledge in statistical analysis of device output and have experience with failure analysis. The role holder will work
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invites applications from candidates with a robust foundation in data science, modelling, and/or engineering, and a keen interest in deploying data analysis and artificial intelligence (AI) to solve real
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questions for research interviews. Conducting a series of semi-structured interviews at UoN. Transcription and analysis of qualitative data. Attending research team meetings. Contributing to publication
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) in an appropriate discipline. Subject Area Computer Science & IT, Electrical & Electronic Keywords Artificial intelligence, floating-point arithmetic, numerical analysis, computer arithmetic, machine
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international collaborations with clinicians, regulators, policymakers, and industry partners. You must have a strong background in machine learning, computer vision, and medical image analysis, with publications
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interpretation of the data generated and that’s where this project comes in. You’ll be applying metagenomic techniques to respiratory samples and developing analysis and interpretation approaches that facilitate
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As a PhD student within the Economics Division, you will have access to a broad programme of research training opportunities. These include advanced methods courses, data skills workshops, and an
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bottleneck in the screening process. This PhD project will address this through deep integration of scanning probe electrochemistry, optical microscopy and machine vision, to develop a system that can
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desorption mechanisms of various FFA on different type of metallic surfaces as a function of temperature and concentration. The modelling data and principal component analysis will be used to build property
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
predictive and explainable digital twins. The core challenge this PhD will tackle is how to help digital twins make sense of complex, messy maintenance data and turn it into clear, useful insights