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for cardiovascular disease in this patient group using linked electronic health record data. The post offers an excellent opportunity to develop expertise in risk prediction methodology for electronic health records
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diseases, immune-modifying treatments and dementia risk using linked electronic health records. The post offers an excellent opportunity to design and conduct studies involving analysis of large-scale health
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, relevant experience in computer-based statistical analysis and presentation of results, demonstrated proficiency in a coding language used for data analysis, such as Python or R, strong quantitative skills
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position informally are encouraged to contact Prof. Daniel J Brockman +44 (0) 1707 666281 or email: dbrockman@rvc.ac.uk
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in partnership to achieve excellence in public and global health research, education and translation of knowledge into policy and practice. An exciting opportunity has arisen in the LSHTM Electronic
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have a postgraduate degree, ideally a doctoral degree, in a relevant field and experience in computer-based analyses and presentation of experimental data. The successful applicant would have a proven
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methods, relevant experience of handling administrative or routinely collected electronic health record data, for example Hospital Episode Statistics (HES), and of undertaking advanced quantitative analyses
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contact Dr Robert Priest, Head of Department on robert.priest@rhul.ac.uk For queries on the application process the Human Resources Department can be contacted by email at: recruitment@rhul.ac.uk Please