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Research Fellow in Statistical Methodology

Department of Medical Statistics

Salary:  £39,304 to £43,760 per annum, inclusive.
Closing Date:  Monday 26 August 2019
Reference:  EPH-MS-2019-06

The London School of Hygiene & Tropical Medicine is a world-leading centre for research and postgraduate education in public and global health. Our mission is to improve health and health equity in the UK and worldwide; working in partnership to achieve excellence in public and global health research, education and translation of knowledge into policy and practice.

We have an exciting opportunity for a statistician, or a researcher in a related discipline, to undertake biostatistical methodological research relating to high-dimensional confounder adjustment in data taken from electronic health records. As well as undertaking methodological research, the successful candidate will have opportunities to collaborate on a range of high-profile applied epidemiological research projects.  The post will involve diverse opportunities in research and training and to teach postgraduate students in the MSc in Medical Statistics and the MSc in Health Data Science.

This work is motivated by studies using primary care health data to investigate harms and benefits of commonly prescribed drugs such as proton pump inhibitors, where confounding by indication has provided strongly biased results. Data-driven methods incorporating information from patients’ entire medical history show promise. Optimal approaches to transforming medical histories to variables (features), modelling very large numbers of confounders appropriately and the role of machine learning methods within these steps, are still to be determined. 

Applicants will need a postgraduate degree in medical statistics or a related discipline (for example statistics, machine learning, mathematics, data science). A PhD in medical statistics, or a related area, is desirable. Previous research experience in a health-related area would be an advantage but not essential. It is essential that the post-holder will have experience of statistical programming and an aptitude for methodological research.  Further particulars are included in the job description.  

The post is full-time and fixed term, available immediately and is funded until 31 July 2022 in the first instance .The salary will be on the Research Fellow Grade 6 in the range £39,304 - £43,760 per annum (inclusive of London Weighting).  The post will be subject to the LSHTM terms and conditions of service.  Annual leave entitlement is 30 working days per year, pro rata for part time staff. In addition to this there are discretionary “Director’s Days”. Membership of the Pension Scheme is available. The post is based in London at the London School of Hygiene & Tropical Medicine.

Applications should be made on-line via our website at http://jobs.lshtm.ac.uk. Applications should also include the names and email contacts of two referees who can be contacted immediately if shortlisted. Online applications will be accepted by the automated system until 10pm of the closing date. Any queries regarding the application process may be addressed to jobs@lshtm.ac.uk

The supporting statement section should set out how your qualifications, experience and training meet each of the selection criteria. Please provide one or more paragraphs addressing each criterion. The supporting statement is an essential part of the selection process and thus a failure to provide this information will mean that the application will not be considered. An answer to any of the criteria such as "Please see attached CV" will not be considered acceptable. 

Further details:    Job Description    

The London School of Hygiene & Tropical Medicine is committed to being an equal opportunities employer. We believe that when people feel respected and included, they can be more creative, successful, and happier at work. While we have more work to do, we are committed to building an inclusive workplace, a community that everyone feels a part of, which is safe, respectful, supportive and enables all to reach their full potential.


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