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Field
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of the PhD will be open for the student to refine. We anticipate a mix of field data collection, laboratory and Sphagnum growth experiments, alongside a strong modelling component. The work will focus
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to the full extent. The objectives of this project are i) to quantify the carbon footprint of silage production under different management practices using data collected in farm audits undertaken across the UK
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relevant equipment and travel. Application Information Applicants should apply via the University’s admissions portal (EUCLID) and apply for the following programme: https://postgraduate.degrees.ed.ac.uk
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an Ahmed body will be used as the baseline. Numerical studies will be performed using commercial CFD software. A correlation between experimental and numerical data will be determined. This project
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dysfunction in Alpers’ syndrome. The student will receive training in a wide range of techniques including tissue culture, immunofluorescence and quantitative microscopy, metabolic assays, and data analysis
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quantification and data science. Potential investigation areas: • Enhancing Monte Carlo and Markov Chain Monte Carlo (MCMC) with reinforcement learning. • Developing adaptive tuning and continual learning
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and data analysis. You will be working at the interface of chemistry and chemical engineering to improve the enrichment process. This will involve investigating different extractants, solvents, and
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: Applicants must meet the minimum English language requirements. Further details are available on the International website . Funding information: The studentship is for 4 years full-time and provides a tax
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reliability and maintenance strategies. Filter Rig: An experimental setup to study filter clogging phenomena, allowing for the collection of data to develop and validate prognostic models for filter
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mitigating jamming and spoofing threats in real-time. Integration of Trusted Execution Environments (TEEs): Investigate the use of TEEs to create secure zones within embedded systems, facilitating secure data