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University of Exeter
Postdoctoral Research Fellows - Statistician/Epidemiologist/Quantitative Social Scientist (Ref. R60424)
We are pleased to offer two outstanding opportunities for early-career researchers with exceptional statistical skills who wish to apply these skills to projects that will provide evidence to influence policy and practice in the field of ageing and dementia. One role is available from July 2018 on a full-time fixed term basis until December 2020 with an expected extension to December 2022 subject to review of progress with the project in 2020. The other role is available immediately on a full-time, fixed term basis for two years from the date of appointment (this may be extended depending on funding).
Location: Exeter
Salary: Salary will be £34,520 - £36,613 per annum subject to knowledge, skills and experience.
Deadline: 22 May 2018
Focus of the research: These two posts will focus primarily on the IDEAL programme (see IDEAL is a longitudinal cohort study of people living with dementia and carers that aims to identify what can be done to enable people to ‘live well’ with the condition. The IDEAL team is currently undertaking the third annual wave of data collection. IDEAL began in 2014, funded by an ESRC/NIHR large grant, and has been funded to continue for three further annual waves of data collection as an Alzheimer’s Society Centre of Excellence. There may also be opportunities to work on other REACH projects.

Key aspects of the role: - You will work with investigators and research team members to develop statistical analysis plans and carry out complex statistical analyses and modelling, using both cross-sectional and longitudinal data - You will oversee the statistical aspects of data capture and data management. - You will have opportunities to participate in the development of bespoke statistical methods building on recent methodological advances. - You may also contribute statistical skills to systematic reviews and other initiatives such as evaluation of existing and newly-developed measures and implementation outcomes. - You will both lead on and contribute to study-related publications and you may be involved in preparing funding applications.

About you: - To apply for these posts you must have (or be near to completing) a relevant PhD or equivalent qualification. - You will need advanced statistical and methodological skills (for example knowledge of one or more of the following: longitudinal data analysis, structural equation models, Bayesian methods, latent class modelling or item response theory). - You will need excellent written and verbal communication skills and the ability to work collaboratively, supervise the work of others, advise team members on statistical and methodological issues, and act as team leader as required. - You will have, or will be prepared to rapidly gain, sufficient knowledge of psychological and social aspects of ageing and/or dementia to enable you to develop and implement projects and supervise others. - You will have a strong track-record of publications in relation to your career stage.

Please ensure you read our Job Description and Person Specification for full details of this role (found on our website). In your application please indicate clearly how you meet the essential and desirable criteria for the post.

We welcome applications from candidates interested in working part-time hours or job-sharing arrangements.

This role may be subject to additional background screening.

The University of Exeter is an equal opportunity employer. We are officially recognised as a Disability Confident employer, an Athena Swan accredited institution and a Stonewall Diversity Champion. Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented in the workforce.

Associated Download(s):
How to Apply
For further information please contact Professor Linda Clare on e-mail or Dr Sharon Nelis on Interviews are expected to take place on 18th June 2018. Applications should be made via our website. For more information and to apply online please go to Please quote reference number R60424 in any correspondence.
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