The Newton Gateway to Mathematics is pleased to be working with the United Kingdom Health Security Agency (UKHSA), who are seeking 7 PhD Students with strong backgrounds in data analysis, Statistics, Mathematics, Biological Sciences, or Social Research, to join their Early Career Researcher (ECR) programme as ECR Analysts - Advanced Epidemiological Modellers for 3 months.

This ECR Programme aims to improve organisational capability by bringing in specialist and expert skills to UKHSA and serves to attract a pipeline of future talent and strengthen organisational links with academia. As well as work experience, the placement will also provide candidates with a pastoral and development programme, together with opportunities to expand their technical skillset and directly influence public health security policy within the UK.

There are 7 roles available in the Public Health Science: Infectious Disease Modelling team within the All Hazards Intelligence directorate. The start dates are staggered throughout the year, with at least two ECRs in post during each placement phase. Phase 1 will begin in end of February 2024, Phase 2 in May 2024, and Phase 3 in September 2024. The start dates are between 20th February 2024 and 1st October 2024. Depending on the postholder’s skill set, preference and the UKHSA’s needs, the postholder could be placed into any of these phases. Funding will be provided to the postholder’s host University to cover 3-months of stipend payments, allowing PhD deadlines to be extended accordingly.

The posts will provide scientific support in infectious disease modelling to the epidemiological investigation of incidents and outbreaks, including COVID-19 and Mpox, in collaboration with partners. This will include technical and analytical aspects of epidemiological outbreak investigations and modelling. The posts will also provide scientific support to the UKHSA’s developing work packages in modelling climate-sensitive infectious diseases, in collaboration with the Centre for Climate and Health Security and academia. This will include technical aspects of ecological modelling, epidemiological modelling, and geospatial data analysis.