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collaboratively as part of a research team, with strong organisational and time management skills. Desirable criteria Understanding of patient and public involvement and engagement (PPIE) processes, with experience
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Understanding of patient and public involvement and engagement (PPIE) processes, with experience contributing to or evaluating PPIE activities. Experience in/understanding of eye-tracking and/or EEG data
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at each stage of the recruitment process. *Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In
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the Job Description document, provided at the bottom of the page. This document will provide information of what criteria will be assessed at each stage of the recruitment process. *Please note that this is
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College of Chemistry and Molecular Engineering, Peking University | Cambridge, England | United Kingdom | about 8 hours ago
with the global mid-ocean ridge system, shape surface volcanism and associated ecosystems. The Galápagos Islands provide an archetypal setting for investigating these processes. By exploring plume-ridge
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nanocomposites ¿ Manufacture prototypes using the new materials and evaluate their performance ¿ Investigate science underlying the material functions and processes ¿ Work with internal and
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. They will work closely with the wider project team to ensure that survivor perspectives shape the research process and outcomes, and will contribute to dissemination through academic publications, conferences
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human trophectoderm development. The aim of this project is to test the functional requirement for signalling pathways in trophectoderm development. We have recently identified a number of candidate
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analysing qualitative data, and leading on the development of the theoretical framework. They will work closely with the wider project team to ensure that survivor perspectives shape the research process and
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Project The Adaptive Design for AI-Driven Processes in Transforming Dynamic Landscapes (ADAPT) project develops scalable, data-driven design methodologies that transform dynamic environmental processes