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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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Failure Analysis of Composite Sleeves for Surface Permanent Magnet Electrical Machines This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites
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analyses by age, ethnicity, and index of multiple deprivation will be performed. The second stage of the study will involve the analysis of prospectively collected EQ-5D-5L data from a cohort of patients to
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integrated Masters, a BSc + MSc or a BSc with substantial research experience will be highly advantageous. Experience in organic/polymer synthesis and/or material analysis will also be beneficial. EU
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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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/or engineering, and a keen interest in deploying data analysis and artificial intelligence (AI) to solve real-world problems in the built environment. The project will advance the capabilities of Pulse
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-derived criteria. A scoping review, alongside initial semi-structured interviews and focus group transcripts subjected to thematic analysis, will build a picture of what key stakeholders want. Clinic
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on numerical aspects of the network model analysis. Being part of the wider Mathematical Neuroscience research theme within the School of Mathematical Sciences which currently includes 7 members of academic
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that present significant problems for data reduction and analysis. This PhD project, in close collaboration with researchers at ISIS Neutron and Muon Source and University of Nottingham, will address this by
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/or dynamic analysis of mechanical/robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the-loop