Research Associate (Medical Statistics and Data Analysis) in The NIHR applied Research Collaboration for Greater Manchester (Digital Health Theme)

Updated: 25 days ago
Location: Manchester, ENGLAND
Deadline: 26 Sep 2019

The University of Manchester wish to appoint a Research Associate in Medical Statistics and Data Analysis to join the Digital Health Research Theme within the NIHR Applied Research Collaboration for Greater Manchester (NIHR-ARC GM), based at the University of Manchester.  This position offers the opportunity to contribute to the implementation and evaluation of innovative digital interventions in health and social care across Greater Manchester, aimed at disease prevention; self-management; integrated and personalised care; and healthy ageing. Alongside qualitative /ethnographic studies, quantitative research methods will play a key role in understanding how these interventions are being used; whether they are safe and effective; and how they could be optimised.

The NIHR ARC-GM (funded for 5 years) is collaboration between the University of Manchester and the health and care system of Greater Manchester. Our work is directly informed by the needs of both this system and the local population. Our over-arching goal is to improve the health of the GM population and the quality and sustainability of the health and social care they receive. We will achieve this by co-producing excellent research in areas prioritised by the system and by enhancing its impact through supported implementation into policy and practice. 

The successful applicant will work with Prof Niels Peek (Line Manager) as well as other members of the Digital Health Research Theme and will be based in the Division of Informatics, Imaging and Data Science in the Faculty of Biology, Medicine and Health. This is a full-time post and the post-holder will be office-based at the University of Manchester campus on Oxford Road. 

Candidates will need a PhD in statistics, computer science, epidemiology or related discipline; experience in manipulating and analysing electronic health record data; significant statistical modelling and programming experience and experience in researching complex digital interventions in the NHS. 

The School is strongly committed to promoting equality and diversity, including the Athena SWAN charter for gender equality in higher education. The School holds a Silver Award which recognises their good practice in relation to gender; including flexible working arrangements, family-friendly policies, and support to allow staff achieve a good work-life balance. We particularly welcome applications from women for this post. All appointment will be made on merit. For further information, please visit:

https://www.bmh.manchester.ac.uk/about/equality/

Please note interviews will take place on the afternoon of Monday 30 September 2019.
Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Enquiries about the vacancy, shortlisting and interviews:
Name: Niels Peek
Email: Niels.Peek@manchester.ac.uk

General enquiries:
Email: hrservices@manchester.ac.uk
Tel: 0161 275 4499

Technical support:
Email: universityofmanchester@helpmeapply.co.uk
Tel: 0161 850 200


This vacancy will close for applications at midnight on the closing date.

Please see link below for the Further Particulars document which contains the person specification criteria that you should address in your application.


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