We wish to appoint a talented, enthusiastic and self-motivated Research Associate in Applied Medical Statistics join the Digital Health Research Theme within the NIHR Applied Research Collaboration for Greater Manchester (ARC-GM), based at the University of Manchester.
The NIHR ARC-GM aims to implement and evaluate a range of digital interventions in health and social care for disease prevention, self-management, and integrated and personalised care, and healthy ageing. The overall purpose of the position is to assist in these activities through statistical analysis of health data. In all activities, strong synergy will be sought with the other NIHR GM ARC themes.
All evaluations will have both qualitative and quantitative components, with qualitative and quantitative researchers working closely together. As the post holder, you will lead the quantitative aspects of the research. You will use methods from statistics, epidemiology, and machine learning, applying them to real-world health data to understand how interventions are implemented in practice and which factors affect their adoption, use, safety, and effectiveness. Data sources will be electronic health records (and other routinely collected NHS data) and personal health datasets collected through smartphones and wearable devices.
You will need excellent skills and experience in analysing health data, using statistical modelling and programming techniques. You will also have a track record of productivity evidenced through peer reviewed journal publications.
You will at least be involved in the following projects:
Further projects will be determined in collaboration with the Greater Manchester Health and Social Care Partnership, Health Innovation Manchester, public representatives, further health and social stakeholders, and collaborators within the NIHR GM ARC.
The post holder will be part of a large group of health data scientists within the Division of Informatics, Imaging and Data Science, consisting of statisticians; epidemiologists; computer scientists; and bioinformaticians. Through the University of Manchester's Data Science Institute, the group has close links to the Alan Turing Institute, the UK's National Institute for Data Science and AI.
We have a genuine commitment to equality of opportunity for our staff and students, and are proud to employ a workforce that reflects the diverse community we serve. As the School is committed to the principles of the Race Equality Charter Mark, we would particularly welcome applications from the black, Asian and minority ethnic (BAME) community who are currently under-represented at this level in this area. All appointments will be made on merit.
The post-holder will be office-based at the University of Manchester campus on Oxford Road. However, during the pandemic many staff are either working from home or a hybrid of home and office working.
As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.
Our University is positive about flexible working – you can find out more here
Blended working arrangements may be considered
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: Prof Niels Peek
Email: niels.peek@manchester.ac.uk
General enquiries:
Email: hrservices@manchester.ac.uk
Technical support:
https://jobseekersupport.jobtrain.co.uk/support/home
This vacancy will close for applications at midnight on the closing date.
Please see the link below for the Further Particulars document which contains the person specification criteria.
