Research Associate in Epidemiology

This is an exciting opportunity to work on an National Institute of Health Research (NIHR) funded programme of work focussed supporting an Advanced Fellowship on evaluating the safety of medications and personalised risk prediction. We will use a range of study designs and statistical models to evaluate safety outcomes of public health interest, focussed on patients receiving prescription opioids. The successful candidate will take a leading role in the analysis of research studies utilising primary and secondary care electronic health records (EHRs) and join a growing team of analysts and methodologists working in this field based in the Centre for Epidemiology Versus Arthritis (CfE). The CfE is an internationally recognised Centre of Excellence for musculoskeletal epidemiology in the UK and a part of the Centre for Musculoskeletal Research (CfMR), a European Alliance of Associations for Rheumatology (EULAR) Centre of Excellence. They will collaborate on projects in a multidisciplinary research environment, be supported in their professional development, whilst working with colleagues also from the Centre of Health Informatics, the NHS and international collaborators.

Project Rationale:

Opioid utilisation for non-cancer pain and related adverse outcomes have reached epidemic proportions in the US, Canada with rising trends in the UK (1-4). Opioids have led to a major societal burden in North America; however, less is known about their utilisation in vulnerable subgroups and safety in Europe and the UK. Some opioid users may be particularly vulnerable to related harms due to specific individual factors such as older age, specific comorbidities and polypharmacy. Maximising benefits and limiting risks of treatment for such patients is therefore a national public health priority.

We will use state of art statistical models and novel study designs to evaluate the comparative safety of opioids in relation to short term and long-term safety outcomes. We will also use traditional statistics and machine learning methods to develop and validate prediction models for key safety outcomes. The programme of work will move risk estimation towards personalised risk, whereby patients can be informed of their individual risk of side effects before starting the drug. Although focussed on opioids, the skills and methods developed will have wider application for investigating the safety of other medications.

Overall purpose of the role:

Based at the CfE, you will work with established primary care EHRs from the Clinical Practice Research Datalink (CPRD) as well as emerging linked secondary and primary care EHRs from Salford Royal NHS Foundation Trust, a digitally mature NHS hospital with EHRs established since the early 2000’s.

We are seeking an outstanding researcher with excellent statistical analysis skills to join the team. You will gain experience in using a range of platforms using state-of the art statistical methods to address clinically important research questions, with potential to drive improvements in future prescribing of opioids and impact policy. Prior to this, preparation of drug exposure data will be performed using transparent and reproducible processes, following preceding work led in CfE (5.) Prior experience in epidemiology would be well suited for this role, although we encourage and welcome applications from people with a background in biostatistics, mathematics, and other numerate disciplines. You should have a thorough understanding of epidemiological concepts, of applied statistical methods and have excellent communication skills. The post is initially for one year, with a view to extend for another two years when relevant programme objectives are met. Development towards post-doctoral fellowships will be supported where appropriate also.

The School/Department is strongly committed to promoting equality and diversity, including the Athena SWAN charter for gender equality in higher education. The School/Department 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/                                                                             

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: Dr Meghna Jani

Email: meghna.jani@manchester.ac.uk

General enquiries:

Email: People.Recruitment@manchester.ac.uk

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

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