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PhD Studentship in Aeronautics: How offshore wind farms and clouds interact: Maximising performance with scientific machine learning (AE0078) Start: Between 1 August 2026 and 1 July 2027
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learning and machine learning for biological data Sequence and structure analysis of large-scale datasets Functional annotation and evolutionary analysis Collaborative research with experimental virology
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-the-fitness-costs-of-drug-resistance-in-cancer for further information. The project aims include: Project aims Barcode a panel of cancer cell lines to enable genetic lineage tracing Design a large-scale
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PhD Studentship: Nanopore Technology for Rapid and Accurate Measurement of Antibiotic Concentrations
environments. Training and Student Development: The student will gain hands-on experience in: Molecular biology and aptamer engineering Nanopore fabrication and single-molecule sensing Data acquisition and
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Further information *Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £43,863- £47,223 per annum. The posts are available from 05
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stability as system strength continues to decline. Building on existing frameworks such as the WECC Composite Load Model (CLM), you will develop and validate data-driven methods for load identification and
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Please note, this is a PhD Scholarship co-funded by Foundations, the National What Works Centre for Children and Families and the biggest funder of evaluation research in early interventions