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project developing Bayesian causal inference methods for mediation analysis using Electronic Health Records (EHR) data. The Research Fellow will design and implement Bayesian methods and software
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including mental health using linked electronic health records data. The post offers an excellent opportunity to design and conduct studies involving analysis of large-scale health data from the UK using
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prevention and improve burden estimates. The post-holder will support the team with co-ordination activities, data management and analysis, and assist with the drafting of manuscripts and collating feedback
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Assistant Professor) to support primarily two new UKRI projects with additional ad hoc statistical analysis and epidemiological interpretation for projects in the thriving laboratories of Professor Chris
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Nigeria. The post holder will be responsible for field data collection in Nigeria, data analysis and writing academic reports/articles for the project outcomes. The post holder will be mainly responsible
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Salvador, Brazil. The post-holder will also contribute to the laboratory analysis, data cleaning and management, and data analysis and write-up a study to assess environmental exposures to enteric pathogen
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analysis of large-scale cohorts. The job requires strong skills in statistical inference and probability, and knowledge of designs and analytical methods for cohort studies. The candidate must have
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datasets. Some experience with observational data analysis and familiarity with risk prediction is required. A commitment to multi-disciplinary and collaborative working is essential. Experience using
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, conducting simulation studies, analysis of datasets from economic and social research studies, software implementation and delivery of workshops. The Research Fellow will be supervised by Prof. Jonathan
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for this and other related grants held by the group, including coordinating meetings with coinvestigators and stakeholders, contributing to writing of publications and contributing to quantitative data analysis