| Location: | Oxford |
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| Salary: | £49,119 to £55,031 per annum (pro-rata). Research Grade 8 |
| Hours: | Full Time |
| Contract Type: | Fixed-Term/Contract |
| Placed On: | 12th May 2026 |
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| Closes: | 22nd June 2026 |
| Job Ref: | 186159 |
Location: New Radcliffe House, Radcliffe Observatory Quarter, Woodstock Rd, Oxford, OX2 6GG
At the heart of this role is the prevention of babies dying around the time of birth. You will work on the national Perinatal Mortality Review Tool (PMRT) programme which focuses on understanding why babies die and working to prevent future deaths. We have developed the national PMRT to support hospitals in the UK in carrying out robust reviews when babies die, to learn lessons to help prevent future deaths. This post is central to maximising the benefits of PMRT review for parents, supporting hospitals, and driving further developments of the PMRT.
We are looking for an experienced quantitative researcher with project management skills to join the team responsible for delivering the national PMRT programme. This varied role will be central to the continuing success of the PMRT programme. The post-holder will have a range of responsibilities including the, largely quantitative, analysis of national PMRT data; supporting the further development of the PMRT; supporting parent, public and patient involvement and engagement; running and further developing the PMRT on-line training for users; and driving forward the delivery of the programme.
The National Perinatal Epidemiology Unit is an internationally recognised, multi-disciplinary research unit based within the in the Nuffield Department of Women's & Reproductive Health (NDWRH) at the University of Oxford. The Unit undertakes research about pregnancy, childbirth and newborn babies.
To be considered for this role you will hold, or be close to completion of, a PhD/DPhil in a health-related science, or hold another postgraduate qualification with substantial relevant experience; have experience of the analysis of quantitative data, including using logistic regression and other data modelling techniques; and project management experience. You will also have a track record of publication of papers and writing reports, as well as excellent organisational, interpersonal and communication skills.
Applications for flexible working arrangements are welcomed and will be considered in line with business needs.
You will be required to upload a CV and Supporting Statement as part of your online application. The Supporting Statement should clearly describe how you meet each of the selection criteria listed in the job description.
This role is full time (part-time considered) and is fixed term until 30 September 2027.
The closing date for applications is 12.00 noon on Monday 22 June 2026. Interviews are expected to take place on Monday 6 July 2026.
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