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theory of decision-making under both risk and delay - Affective Imagination Theory (AIT). The main research objective of the grant is to combine formal and computational models with rigorous empirical
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cognition and emotion processing. We invite applications from individuals with a background in human experimental psychology (participant recruitment, experimental testing, data analysis) and with a PhD in
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(CMHPE), utilising their mixed methods their mixed-methods (ideally qualitative and quantitative) expertise. The role includes planning, coordinating, executing, and reporting on evaluation and improvement
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Analyse and interpret qualitative data using appropriate methods (e.g. thematic analysis) Use qualitative software (such as NVivo) to manage and code data Apply knowledge in a way that develops new
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policy briefings Contribute to development of implementation strategies and evaluation plans Supervise students working on related research themes Contribute to developing and refining models, methods, and
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of the project’s four research sites, using feminist, creative, and participatory methods including qualitative interviews, counter-mapping, and Photovoice. They will analyse qualitative data, and
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independently and in close collaboration with in-country partners. The applicant should have an excellent academic track record that includes formal training in microbiology as well as a relevant PhD (public
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annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
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software development is desirable. A PhD, a strong publication record, and excellent technical communication, reporting, and presentation skills are required. Due to the nature of this role, you will be
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obtained or are within 6 months of submission of their PhD. Evidence of implementing Virtual Reality interventions in a statutory health and social care setting. Experience and knowledge of mixed methods