Senior Research Associate (Fixed Term)
We are looking for an ambitious senior researcher to join an internationally renowned research Unit and a team carrying out high profile work at the cutting edge of development and application of Bayesian methods to infectious disease epidemiology.
The post-holder will be part of Professor De Angelis' team within the Population Health Theme at the MRC Biostatistics Unit (MRC-BSU). The project, funded by a Wellcome Discovery award in collaboration with the Universities of Oxford and Manchester and the UK Health Security Agency, aims to develop new methods to understand community transmission of respiratory infections using data from the Office of National Statistics (ONS) COVID-19 Infection Survey (CIS).
The ONS CIS is a unique household survey with longitudinal follow up of over 500,000 participants who were regularly swabbed for SARS-CoV-2 infection at over 10 million visits, with positive swabs sent for whole-genome deep sequencing. A subset of participants were additionally tested for RSV and influenza. Over 100,000 high-quality SARS-CoV-2 sequences are available, linked to data on behaviour, symptoms and vaccination status collected at each visit. The ONS CIS was regularly used to estimate prevalence of SARS-CoV-2 in the population to inform policy during the pandemic (e.g. Coronavirus (COVID-19) Infection Survey, UK: 3 December 2021). However, these data remain under-utilised.
The post-holder will lead research to exploit the ONS CIS data collection to better understand community infection and transmission. Starting with SARS-CoV-2, the main task is to develop new methods to jointly estimate incidence and transmission, integrating the rich epidemological and genomic data available. This will allow quantification of changes in transmission across pandemic waves while disentangling the contribution of different viral lineages. An important constraint in this project is the need for individual-level data to remain within a computationally limited secure research environment, so innovative approaches to computation will be key. Outputs will include new estimation tools and inform the design of future population surveys, contributing to the pandemic preparedness agenda.
The successful candidate will have a PhD in a strongly quantitative discipline, and a record of previous postdoctoral research experience at the level of Research Associate. Specialist knowledge in Bayesian statistics and strong computational skills are essential as is an ability to produce high-quality academic outputs, experience of building, strengthening and sustaining positive collaborative relationships and an enthusiasm for collaborating with non-statistical scientists. Experience in infectious disease transmission modelling is also required. The successful candidate will be supported in their career development with formal courses and on-the-job training. MRC-BSU is one of Europe's leading biostatistics research institutions. Our focus is to develop and apply new analytical and computational strategies for the challenging tasks facing biomedicine and public health. The Unit is situated on the Cambridge Biomedical Campus, one of the world's most vibrant centres of biomedical research, which includes the University of Cambridge's Clinical School, two major hospitals, the MRC Laboratory of Molecular Biology, and the world headquarters of Astra Zeneca.
The Unit is actively seeking to increase diversity among its staff, including promoting an equitable representation of men and women. Applications from women, from minority ethnic groups and from those with non-standard career paths are especially encouraged. Appointment will be made on merit.
The Biostatistics Unit is committed to supporting hybrid working for all staff, but we do expect that staff will work from the office on a regular basis to help integration and to build our exceptional scientific community. Working entirely from the office is possible.
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Fixed-term: The funds for this post are available until 31 March 2028 in the first instance.
Please ensure that you upload a covering letter and a CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.
Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.
The closing date for applications is: 25th September 2024
The interview date for the role is: To be confirmed
Please quote reference SL43249 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.