Job summary

The Vaccine Impact Modelling Consortium (www.vaccineimpact.org) is a major collaborative initiative based within the MRC Centre for Outbreak Analysis and Modelling at Imperial College London and funded jointly by the Gates Foundation and Gavi.

The VIMC secretariat collates and aggregates estimates provided by consortium members to inform funders and communicate vaccine impact estimates to stakeholders to help fundraising for childhood vaccination in low and middle-income countries and target existing resources optimally. A vacancy has arisen in the secretariat’s science team of 3 full time researchers who collaborate closely with the technical team of 5 software developers to provide the infrastructure for hosting and reporting on the large datasets generated by the consortium.

Duties and responsibilities

The secretariat’s research agenda includes methodological developments, e.g., frameworks to generate ensemble vaccine impact estimates that represent uncertainties in the underlying data sources and model structures, and further novel approaches to improve the quality of the generated estimates. There will be opportunities to spend short periods within Gavi or the Gates Foundation and gain insights into the way these international health agencies work.

We are looking for someone with high potential who will fit well into the highly collaborative team. While the position is advertised as post-doctoral Research Associate (level B), we could offer employment as Research Fellow (level C) for a candidate with suitable experience. We would also consider exceptional candidates pre-PhD (as Research Assistant, level A).
Salary Range

£32,380 - £34,040 per annum (Research Assistant)
£36,800 - £44,220 per annum (Research Associate)
£40,840 – £53,400 per annum (Research Fellow)

Essential requirements

The successful candidate will have a PhD (for appointment to Research Associate or Fellow) or MSc (for appointment to Research Assistant) in a highly quantitative subject or equivalent experience. Strong technical skills including experience of mathematical or statistical modelling and programming (preferably in R) are essential.

Further information

This post is full time and fixed term for 3 years. Imperial College is supportive of flexible working. The College is happy to discuss the possibility of implementing such arrangements for this post, with suitably qualified people, subject to operational requirements.

Should you have any queries please contact: Dr Tini Garske (t.garske@imperial.ac.uk)