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processes associated with CIN [1], leveraging single-cell DNA sequencing understand CIN heterogeneity [2], and development and implementation of machine learning and AI models to imaging data [3]. The student
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Supervisor: Professor Richard Gilbertson and Dr Giulia Biffi For further information about the research group, please visit biffilab.wordpress.com . Project details Cancer-associated fibroblasts
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performed annually in the UK. However, about 20% require revision within 15 years due to complications like implant loosening, dislocation, and fractures caused by suboptimal implant positioning. With primary
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remain largely unexplored. This research will be carried out by using the world-leading research facilities (high temperature experiment, advanced characterisation and modelling) at the Advanced Steel
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models, making the use of data-driven approaches a promising direction. This PhD project will investigate the use of data-driven and machine learning approaches, both measurement based but also model based
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Deadline extended: 30 October 2025 (originally 29 September 2025) A fully funded 3-year PhD is available in the School of Computer Science and Engineering (SCSE), Bangor University. The project will
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on Africa, including Zimbabwe where we have previously collected pilot data with collaborator Dr McDonald Matika. Although potential second countries in each continent have already been identified, the PhD
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This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26; subject to annual uplift
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@ch.cam.ac.uk , including 'PhD CI ¿ October 2026' in the subject. How to apply Please apply via the University Applicant Portal. For further information about the course and to access the Applicant Portal, click
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‘Research Area' field blank select ‘PhD Energy Materials' as the programme of study You will then need to provide the following information in the ‘Further Details’ section: a ‘Personal Statement’ (this is a