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research programme funded by the Academy of Medical Sciences Springboard award. This project aims to explore the role of these neighbouring glycoproteins in neurotrophin-mediated neuronal development as
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/ developing research profile and/ or respected national/ international profile in mixed methods around human-computer interaction PhD or equivalent in relevant subject area or the equivalent in professional
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programme. To acquire, analyse, interpret and evaluate research findings/data using approaches, techniques, models and methods selected or developed for the purpose. To establish a national reputation and
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attracts some of the very best students from around the world to its excellent undergraduate, Masters and PhD programmes. All of our academics also contribute to School administration. We believe that every
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’ or ‘internationally excellent’. The highly research active SP Section comprises 13 permanent academic staff with research interests in Bayesian computational statistics and machine learning, uncertainty quantification
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purposes. We are looking for a confident, organised researcher who can evidence: • A PhD, or equivalent in mathematics, theoretical physics or a relevant branch of engineering. • OR near to completion
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and the manager of your substantive post, if you are already undertaking a secondment role. The Leverhulme Trust’s funding regulations mean that individuals will have needed to have submitted their PhD
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leadership contribution to the running of the BMBS programme providing academic oversight of the Advanced Clinical Practice component of the curriculum. This is a 0.2 FTE role which can be undertaken flexibly
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of sterile and infected single and co-cultures of immune and stromal cells, and correlative data analysis including surface characterisation of biomaterials. Candidates must have a PhD submitted (or close
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-based role focusses on electromagnetic design, computational modelling (e.g., COMSOL, CST, ANSYS), dielectric characterisation, and testing that help to bridge the gap between laboratory-scale research