Research Associate - Statistician / Data Scientist

Closing Date : 25/11/2016
Employment Type : Fixed Term
Duration : Available with immediate effect until 31 July 2018 in the first instance
Faculty / Organisational Unit : Biology, Medicine & Health
School/Directorate : School of Biological Sciences
Division : Musculoskeletal & Dermatological Sciences
Hours Per week : Full time
Salary : £31,706 to £32,004 per annum
Location : Oxford Road, Manchester
Job Reference : BM&H-09078

The Arthritis Research UK Centre for Epidemiology (CfE) at the University of Manchester is seeking a talented and ambitious statistician or data scientist with expertise in the analysis of longitudinal data, including temporally rich data, to help us solve our analytical challenges.  The successful candidate will take a leading role in the analysis of two large longitudinal research studies and join a growing team of analysts and methodologists based in the Centre.  They will collaborate on projects in a multidisciplinary research environment and be supported in their professional development.

Cloudy with a Chance of Pain

Cloudy with a Chance of Pain is an innovative population smartphone study and citizen science experiment to investigate the association between the weather and symptoms in people with arthritis and other chronic pain.  Over 12,000 participants have been recruited since January 2016, amassing over 3.5m symptom scores.  The study has featured on national TV and radio and in national newspapers, as well as gaining global exposure through outlets such as CNN.

The project involves collaboration with the Manchester-based Health eResearch Centre (HeRC), part of the Farr Institute of Health Informatics Research, which combines technology with big health data and modern research methods to improve health for patient and public benefit; the Alan Turing Institute, the London-based national institute for data science ; uMotif a London-based digital health software development company; and the Office for Creative Research (OCR), data visualisation pioneers based in New York. The project has been adopted as one the European City of Science (ECOS) citizen science projects.  Further collaborations with high profile partners are currently being developed, including with some of the biggest names in tech.

You will lead the analysis of the association between hourly weather conditions and daily disease symptoms, as well as analysing the association between passively-monitored physical activity and disease symptoms.

The International Pharmacosurveillance Study

The International Pharmacosurveillance Study, funded by the Canadian Institute of Health Research, is examining the comparative effectiveness and safety of drug treatments using electronic patient records across three countries. The third research question to be addressed, and the focus of this funding period, is the comparative safety of opiates for non-malignant pain. In the UK, this analysis will be conducted using data from the Clinical Practice Research Datalink as well as data from Salford Royal NHS Foundation Trust. The analysis will be conducted across the three international sites using a shared analysis protocol, with additional analyses conducted according to the strengths of the local dataset. For example, the shared protocol will consider all-cause mortality and fractures whilst adjusting for selected confounders available in all sites. Analysis of the Salford data will, for example, allow for adjustment for a propensity to fall, an important confounder which is not measured in other settings.

The post will be line managed by Dr John McBeth (Deputy Director, CfE) with further support and guidance from Prof Will Dixon (Director, CfE), Dr Mark Lunt (Reader in Medical Statistics, CfE) and Dr Jamie Sergeant (Lecturer in Medical Statistics, CfE).

The University of Manchester values a diverse workforce and welcomes applications from all sections of the community

Please note that we are unable to respond to enquiries, accept CV's or applications from Recruitment Agencies.

Enquiries about the vacancy, shortlisting and interviews:

Name: Dr John McBeth or Dr Mark Lunt

Email:  john.mcbeth@manchester.ac.uk    mark.lunt@manchester.ac.uk

General enquiries:

Email: hrservices@manchester.ac.uk

Tel: 0161 275 4499

Technical support:

Email: universityofmanchester@helpmeapply.co.uk

Tel: 01565 818 234

Date of external posting: 26 October 2016

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

Further Particulars

 

This position is now closed. We are no longer accepting applications for this position.