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landscapes including the UK, focusing on challenges that emerge at the intersection of hazard exposure and health service access and availability. Potential projects should involve multi-data analytics (e.g
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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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seeking an academic career in primary care cancer diagnosis, or in data analytics more generally. Main duties and responsibilities Undertake doctoral research on pancreatic cancer diagnosis Finalise project
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | about 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
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for an individual with strong conceptual, analytical, teamwork, and problem-solving skills who has the ability to plan the work independently with minimal supervision and adhere to a time plan to meet the deadlines
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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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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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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | about 2 months ago
addresses critical analytical challenges in CCUS research and has significant industrial impact but also provides a comprehensive training experience for the PhD researcher, preparing them for a successful
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. The ideal candidate will possess strong statistical and analytical skills (as mentioned above) and excellent English communication abilities. He/she should also demonstrate the ability to assess datasets, use
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adverse consequences for overall thermal efficiency and component life (environmental impact, sustainability and safety). While standard analytical models for heat transfer exist for classical cases