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catalytic process. In addition, it is important to improve the student the experimental skill, materials characterization skill and data analysis skill. Student who joins our group will learn the fundamentals
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health, and bioinformatics. You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured
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treatment processes through advanced machine learning, validated against physics-based models and experimental data. System Integration: Integrating the DTs into material and energy balance equations
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factors (learning curve). These will be linked with the CCTA imaging biomarker data (quantitative plaque analysis) that is being collected as part of the EU HORIZON TARGET study to determine personalised
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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skills. Main duties will include: conduct tissue-mechanical and imaging experiments using early avian embryos; acquire and process data; prepare reagents and samples; optimise protocols; program and debug
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science, engineering, mathematics, or related subject) Proficiency in English (both oral and written) Essential to have strong foundations in computer systems through degree courses or equivalent work experience
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Primary supervisor - Dr Rose Davidson Dupuytren’s disease bends the fingers irreversibly into the palm, threatening employment, selfcare and independence. Despite its prevalence, Surgery temporarily
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The research in this doctoral opportunity will investigate the relationship between material elastic and thermal properties by using high resolution digital imaging under dynamic loads. Digital
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propellant space propulsion systems. A significant limiting factor of hybrid propulsion systems is the continuous change in surface area of the propellant grain during the combustion process. This changing O/F