The post provides an opportunity to enhance our capacity in methodology to assist in achieving the research and capacity building aims of the NIHR CLAHRC South London as well as the large scale Quality improvement programme launched by the South London and Maudsley NHS Foundation Trust. These aims include strengthening the quality of methodology through original research and in the delivery of applied projects.
The post will involve a wide range of research activity – including: analysis and modelling of large-scale patient and organisational datasets to inform and evaluate quality improvement policy and intervention; methodological development of novel approaches to analyse such datasets; and development and application of statistical methods to diagnosing problems in care and service delivery.
Applicants should have a PhD in health or medical statistics or a closely related subject (e.g. applied statistics including health research, micro econometrics as applied to programme evaluation) and have a track record of publication and research income generation commensurate with the level of appointment. We would welcome applications from researchers who themselves have experience of using health services.
The post will be located at the IoPPN, Kings College London, Denmark Hill Campus, London and also at the South London and Maudsley NHS Foundation Trust (also on Denmark Hill).
The salary will be paid at Grade 7, £40,523 to £ 44,240 per annum, plus £2,923 per annum London Allowance.
This is a Full-time post.
This post will be Indefinite.
The selection process will include competency based questions, an assessment and a panel interview.
The deadline for applications is midnight on 13 September 2017
For an informal discussion to find out more about the role please contact Professor Nick Sevdalis [log in to unmask] telephone no. 0207 848 0012 or Dr Silia Vitoratou [log in to unmask], telephone no. 0207 848 0309.
Closing date: 13 September 2017
More information: https://www.hirewire.co.uk/HE/1061247/MS_JobDetails.aspx?JobID=77725
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