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are welcome from diverse backgrounds, including physics, chemistry, engineering and material science. We are particularly interested in applicants with a strong preference for hands-on experimental work and a
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the successful candidate embarking on a PhD programme at LSHTM. It is anticipated that the role will lead to a further 18 month funded opportunity at Max Planck Institute for Demographic Research (MPIDR), in
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. We are looking for highly motivated candidates with a strong academic background in computer science, AI/ML, bioinformatics, or related fields such as mathematics and statistics. Informal enquiries
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of Edinburgh and will be jointly supervised by: Dr Dominik Leichtle, School of Informatics, University of Edinburgh Dr Elham Kashefi, School of Informatics, University of Edinburgh Dr Ivan Rungger, National
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skills crossing the disciplines of materials science, biochemistry and analytical chemistry. Techniques will include rheology, materials testing, spectroscopy, surface analysis, molecular weight analysis
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the harmful effects of deepfakes on ordinary people. You will draw on methods from psychology, linguistics, data science, and computer science, such as behavioural analytics, neuroimaging, face and voice
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will have or expect at least a II(i) Undergraduate honours degree or Masters degree (or equivalent) in Materials Science, Chemical Engineering, Chemistry, Physics or related discipline. A background in
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-developed research support base including NET2Zero CDT, and EPSRC Centre for Doctoral Training in Resilient Chemistry: Feedstock to Function. The research programme will use a mixture of computational
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Lead Supervisor name: Andrew Callaway, email: acallaway@bournemouth.ac.uk Project description: This PhD programme will determine the most clinically acceptable methods for emergency response teams
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Engineering have a well-developed research support base including NET2Zero CDT, and EPSRC Centre for Doctoral Training in Resilient Chemistry: Feedstock to Function. The research programme will use a mixture