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Full time research associate with the opportunity to work fully funded for 18 months on ultrasound data transmission across a metal barrier. The research is based on finite element and analytical
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provide real-world insights and infected sample sets for testing. Student will join an enthusiastic, friendly, and supportive group of researchers who are all working on various analytical and experimental
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collaborative project that spans multiple continents. You will contribute to the development of new chronobiological analytics on existing data, design experiments to collect novel chronobiological data, engage
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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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the harmful effects of deepfakes on ordinary people. You will draw on methods from psychology, linguistics, data science, and computer science, such as behavioural analytics, neuroimaging, face and voice
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network analysis of interactions between these features. These pipelines and computational tools will be used to integrate imaging and genetic data, and maps of myelin distribution in the cortical grey
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are particularly interested in new faculty with foci in Marketing Analytics and Digital Marketing. You must be present on campus for the role. Informal enquiries about this position can be made to Professor Stuart
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Chemistry, Physics, Materials Science, or a related discipline. The successful applicant will demonstrate strong interest and self-motivation in the subject and the ability to think analytically and
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. However, as membrane-bound proteins, these receptors are extremely challenging to study using conventional analytical approaches. In this project, you will apply cutting-edge nuclear magnetic resonance (NMR
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 2 months ago
, further exploring the carbon-related impact of polymer breakdown. The project will also incorporate artificial intelligence (AI) and machine learning to optimise degradation processes and data analysis