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Fellow will assist the Principal Investigator, Wellcome Trust Fellow Dr. Elisabeth Yang , in bringing the gap between theory and practice whilst gaining essential skills, experience, and mentoring in
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of Nottingham as part of the new Centre, alongside further role recruitment at King’s College London . At Nottingham, the roles are: Research Fellow in Slavery and War (Concepts and Theories) Research Fellow in
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of Nottingham as part of the new Centre, alongside further role recruitment at King’s College London . At Nottingham, the roles are: Research Fellow in Slavery and War (Concepts and Theories) Research Fellow in
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WMG collaboration with a large vehicle manufacturer. About You You will need a good honours degree and a PhD (or be close to submission thereof) in a relevant subject, and experience of the theory and
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. The successful candidate will also be involved in a broad range of theory, development and empirical work to support the scientific objectives. This role also includes attending project meetings and working with
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behaviour change interventions. Your knowledge of health-related behaviour theories will be essential. You will have experience in recruitment, data collection, and thematic analysis, including focus group
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Candidate We seek an ambitious researcher with a strong foundation in Bayesian theory, machine learning, and mathematical modelling. You should be confident in software development and capable of passing a
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-network theory, assemblages, processual ontologies, regulation and governance). This project benefits from proximity to Prof Tomczak's international prison HEALTH research group, along with its location
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To create and contribute to the creation of knowledge by undertaking a specified range of activities within the research fields of holography, gauge theory and related areas. Role Summary Work within
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on applying multiple quantitative approaches consistent with intersectionality theories to study social inequalities in youth population mental health. Throughout the project, existing data from multiple cohort