Research Assistant/Research Associate (Fixed Term)

The MRC Biostatistics Unit is currently actively engaged in several efforts to understand and mitigate the COVID-19 pandemic: providing evidence on the course of the pandemic; providing evidence for patient care; and designing and analysing interventions on care for COVID-19 patients. Members of Unit are involved in collaborations related to the outbreak in the UK and worldwide, and are members of national scientific and advisory groups. These include Joint Modelling Cell at Public Health England (PHE), Scientific Pandemic Influenza sub-group on Modelling (SPI-M), Royal Statistical Society COVID-19 Taskforce, The Alan Turing Institute (ATI), Joint University Pandemic and Epidemic Response Modelling (JUNIPER) and COVID-19 Genomics UK Consortium (COG-UK).

The purpose of this role(s) is to conduct research and statistical data science as part of one or more of our ongoing analyses of COVID-19 data. A particular focus of the Unit's contribution is how to appropriately model and gain greatest scientific insight from the available data relating to COVID-19. Many key COVID-19 data are challenging to model appropriately and require application of rigorous statistical/data science methods. Under the direction of one or more investigators at the Unit, the postholder(s) will conduct research using appropriate (bio)statistical, data science, or machine learning/AI methods. As appropriate to the specific study, they will have the opportunity to take a central role in shaping and refining research questions; extracting and appraising relevant data from relevant dataset(s); identifying, developing and applying appropriate analysis methods and tools for answering our collaborators' scientific questions.

The studies conducted by the postholder(s) will be in collaboration with our partners in COVID-19 studies, such as for example Public Health England, the Joint Biosecurity Centre and The Alan Turing Institute. These studies have been developed to meet an identified need for improved understanding of aspects of the COVID-19 pandemic, particularly in the UK. The findings of our research will be disseminated to the wider scientific community, policy makers and/or the public as appropriate.

Candidates for Research Associate position will have a PhD in Statistics, or a relevant similar discipline. A Research Assistant appointment will have an MSc in Statistics, or similar relevant subject (or close to completion). Good computational skills, particularly with a statistical programming language, are highly desirable. Prior experience of working with biostatistical/clinical datasets is desirable but not essential. You will also require good communication skills to explain and discuss your work with our collaborators, as well as the ability to write scientific papers.

The MRC Biostatistics Unit is one of Europe's leading biostatistics research institutions. Our focus is to deliver new analytical and computational strategies based on sound statistical principles 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. The Unit therefore especially encourages applications from women, from minority ethnic groups and from those with non-standard career paths. Appointment will be made on merit.

We welcome applications from those wishing to work part-time.

Fixed-term: The funds for this post are available for 12 months in the first instance.

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Closing Date: 3 August 2021

Please ensure that you upload a covering letter and 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.

Please quote reference SL27294 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.

Further information
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