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discipline that combines multiple data sources along the patient pathways and develops real-world evidence to inform future clinical practice. The project will involve developing novel methods such as
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and preventing future losses, but their use remains limited. This project aims to use whole genome sequence (WGS) data from museum samples of Mazarine Blue and Large Copper butterflies to conduct a
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October 2025 Application deadline: 30 June 2025 Please apply here https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx For further information please email Professor Chris Gerada , Dr
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Start date: 1 October 2025 Application deadline: 30 June 2025 Please apply here https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx For further information please email Professor Chris
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. This project will focus on learning about patient experiences and exploring clinical data to improve the care of patients living with kidney disease. What is involved The aim of this research is to improve
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) cluster , which the student will use for their research. The student will also have access to large HPC systems run by DIRAC . The student will be trained in using HPC by the supervision team and at
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. when do we stop modelling? How do we track / score the quality of the model What is the required level of quality over time How can quality be brought to the required level Can Machine Learning, Large
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(Southampton and Denmark), and participation in large-scale testing in Denmark to validate industrial applications of your research. This project is an excellent opportunity for candidates who are interested in
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processing and cognitive adaptation to information overload. It will contribute to a large-scale lab experiment investigating how individuals comprehend and re-tell scientific content under varying conditions
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Abstract: Condition monitoring of industrial equipment, such as turbomachinery, is a complex task that requires accurate and efficient data collection but is often hindered by the equipment's size