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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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and advanced causal inference methods to large-scale multi-omics datasets, national health registers, and other comprehensive health-related data sources. Duties The doctoral position is intended
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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
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in a large project rather than on your own in a single project. The following experience will strengthen your application: Experience in energy storage, organic synthesis, or materials characterization
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data requirements, and lower costs for large-scale modelling tasks. PINNs enhance predictive capabilities and efficiency by combining data-driven methods with physical principles. Unlike traditional
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is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture. The ongoing societal transformation and large green investments in
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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