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- bermet.ishenbekova@ucentralasia.org
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Field
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following skills and experience: Essential criteria PhD in statistical/psychiatric/behavioural genetics or a related academic area with a strong data analysis component Excellent coding skills with a focus on
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monitoring. Conducting experimental work in the laboratory to validate monitoring and data analysis systems. Developing frameworks for sustainability metrics and performance assessment. Analysing data
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of smokers trying to quit using e-cigarettes. Smoking is the leading cause of preventable death worldwide, and a risk factor for many diseases. With an ageing population, the profound economic and health
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on the optimisation of metal hydrides and/or the design of solid-state hydrogen stores and compressors. The candidate must be awarded a PhD by an internationally recognised university in Mechanical Engineering
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looking at the design and analysis of randomised trials of interventions to reduce the risk of vector-borne diseases (e.g. malaria and dengue). The Project offers an interdisciplinary opportunity to work in
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other parts of the country. Therefore, you will have excellent communication and relationship building skills, experience of qualitative research methods and data analysis and an ability to be flexible
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and relationship building skills, experience of qualitative research methods and data analysis and an ability to be flexible and work autonomously. The position requires a mix of skills and behaviours
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of Stirling and Aberdeen and the wider academic team to design and implement social analysis of the cases including regional profiles, interviews and workshops on place-based understanding of Just Transition
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these outcomes vary between those who studied abroad and those who did not. In addition to secondary data analysis, the project also collects and analyses data about study abroad from case study universities
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or Social Prescribing) can serve to reduce loneliness. The research will involve primary data collection, (e.g. online surveys and experiments), secondary analysis of nationally representative datasets (e.g