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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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, and OpenSAFELY, and to develop and apply the new generation of analytical methods to study environmental health risks and climate change. The post will provide opportunities for interactions with
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including malaria, have experience and understanding in using multiple metrics for analysis, experience with design and implementation of study protocols, experience of data analysis in Stata and programming
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the UK—and make a real difference. This role is part of multiple exciting roles that we are recruiting into across a variety of disciplines for this project. About you For this role you will a have a
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research project on cardiovascular risk prediction for people with immune-mediated inflammatory disease. The successful candidate will use advanced risk prediction methods to develop prediction models
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is Prof Cally Tann. We are seeking a Research Fellow in Early Child Development & Disability to coordinate the development, implementation and evaluation of the programme, including: mixed methods
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), and apply these and other related methods in a study comparing the clinical and cost-effectiveness of local versus general anaesthetic for people with a ruptured abdominal aortic aneurysm undergoing
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data from the UK using robust causal inference methods. Based in London at the London School of Hygiene & Tropical Medicine, the post-holder will be embedded within the Electronic Health Records Research
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science methods, ideally to environmental health data, and conducting systematic reviews and meta-analysis. Further particulars are included in the job description. The post is full-time 35 hours per week
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demonstrable experience in analysing datasets such as infectious disease surveillance, applying statistical methods, and interpreting output. Further particulars are included in the job description. The post is