London School of Hygiene & Tropical Medicine
Department of Health Services Research & Policy
Salary:
£39,304 to £44,634 per annum, inclusive.
Closing Date:
Tuesday 13 November 2018
Reference:
PHP-HSRP-2018-08
An exciting opportunity is available for an ambitious statistician / epidemiologist to undertake methodological research related to using linked national datasets. Together with members of a multidisciplinary team of statisticians, epidemiologists and clinicians, novel statistical techniques will be required which will have wide applications for observational studies and for data linkage.
This innovative NIHR-funded 3-year research project will exploit four national clinical datasets including patients who received emergency care for bowel cancer bringing together information about their pathology, peri-operative care, critical care and mortality.
The aim of the research is to develop methods that can be used to construct care pathways with minimum bias from data linkage errors, incomplete capture of patients into each audit, and confounding due to patient selection.
The research will also help to identify which processes of care reduce mortality and complications in bowel cancer patients undergoing emergency surgery. These clinical findings will support hospitals and clinicians to improve patient care and will provide much-needed evidence for new clinical guidelines.
The work will require the successful candidate to use probabilistic linkage methods, advanced regression modelling techniques, multiple imputation, methods and propensity score methods.
The successful applicant will have a Master's degree in medical statistics, epidemiology, operational research or a related field, or equivalent working experience in these fields; experience in independently carrying out statistical analyses of complex health care datasets using statistical techniques such as multiple linear / logistic regression or survival analysis; knowledge and experience of advanced statistical techniques such as multilevel modelling, Bayesian analysis and multiple imputation of missing data; proven ability to contribute to the writing up of research findings for reports and for articles in peer reviewed or professional journals and to communicate results at conferences. Further particulars are included in the job description.
The post is full-time and is based in London until 30 September 2021 (with the possibility of further extension). The salary will be on the Academic pathways Grade 6 scale in the range £39,304 - £44,634 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 position will be based in LSHTM's Tavistock Place campus in Bloomsbury, London.
Applications should be made on-line via our website at http://jobs.lshtm.ac.uk<http://jobs.lshtm.ac.uk/>. Applications should also include the names and email contacts of 2 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 [log in to unmask]<mailto:[log in to unmask]>. Please quote reference REF PHP-HSRP-2018-08.
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.
Please note that if you are shortlisted and are unable to attend on the interview date it may not be possible to offer you an alternative date.
Further details:
Job Description<https://jobs.lshtm.ac.uk/Upload/vacancies/files/572/PHP-HSRP-2018-08%20Job%20description.pdf>
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