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of ethnographic or collaborative methods, as well as contributing to peer reviewed publications/presentations. You will also have excellent organisational skills and the ability to communicate effectively with
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transnational and European history, as well as awareness of current developments and central methods in the field. They have experience with interdisciplinary theories and methods (e.g. Europeanisation, digital
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the mindfulness intervention Analysis of quantitative and qualitative data generated from the project Compiling a report to the funding body at the half way and end of the project Preparing a mixed methods article
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GGR on UK lands. They will also have the opportunity to be part of a consortium project (ERW-GGR) which is itself a component of the UKRI funded Demonstrator phase of greenhouse gas removal techniques
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on breathable nanoscale coating methods for key sorption materials to overcome challenges in their re-use, reliability and energy density. It is a close collaboration with Dr Zhiwei Ma’s group in the Durham
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maternity services in England. To be considered for this role you will hold a PhD in social science or other relevant health related science. You will have experience of ethnographic or collaborative methods
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focus). Skills and experience in qualitative research methods. Research experience and knowledge in either South Asia or South America. An interest in historical, cultural and socio-political contexts. A
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legal research methods Knowledge and familiarity with critical and feminist approaches to gendered violence Knowledge and familiarity with research on online environments, in particular social media
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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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responsibilities will include: Pre-registering data analysis plans; Leading and conducting advanced statistical analyses (e.g., twin/family designs, genomic and epidemiological methods, longitudinal modelling