154 parallel-computing-numerical-methods positions at University of London in United Kingdom
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activities and aims to be an internationally recognised centre of excellence in population health and preventive medicine. The post-holder will be a staff member of the Centre for Evaluation and Methods (CEM
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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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for NHS ethics and Health Research Authority approvals. You will have experience in mixed methods research, particularly with expertise in qualitative methods and be committed to conducting research
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in qualitative research methods and community engagement. The postholder will have an interest in learning new skills and working with colleagues from a range of backgrounds on sexually transmitted
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the working of unsociable hours including early mornings, late nights, weekends, and bank holidays. The successful applicant will be expected to support the development of our group exercise programme through
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within its Saturday programme, Junior Academy. As part of Junior Academy, First String Experience (FSE) is a long-established first access musicianship and bowed string teaching programme for 4 to 7 year
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multidisciplinary team of clinicians, scientists, nurses and support staff, delivering a programme of research relating to traumatic injury, haemostatic resuscitation and optimisation of patient outcomes. The Centre
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mitigation priorities for the UK. Candidates should also be experienced in conducting quantitative research and applying spatio-temporal epidemiologic methods, ideally to environmental health data. Further