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. The student will perform ‘big data’ analysis of patient cohorts including time-based evaluation of the impact of introducing CT-FFR as a national health intervention into a healthcare system. Exploratory
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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institutions (ca. 50:50). Hands-on experience will span battery manufacturing, electrochemical analysis, nanoparticle synthesis, surface chemistry, and safety testing (e.g., ARC). Funding notes: The candidate
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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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animal models and knowledge of interactions between diet, intestinal microbiota and health. Experience with microbiology and gut microbiome analysis is a plus, but not a requirement. Required skills
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via operando liquid-phase transmission electron microscopy (LP-TEM). Your tasks: Self-motivated and independent planning, execution, and analysis of research in the scope of operando electrocatalysis
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computational biology, bioinformatics, systems biology, bioengineering, chemical engineering, or a related discipline Knowledge and experience in the analysis of metagenomics and/or biological high-throughput
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documentation and analysis of research data Development of experimental strategies to investigate and test scientific hypotheses Presentation of research findings and preparation of scientific publications
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background in physics, biophysics, biological physics, or bioengineering. This PhD project will primarily focus on experimental research, which will include data analysis and there is scope for modelling
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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