Research Associate (Fixed Term)

This is an exciting opportunity for an ambitious 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) working on methodologies for nowcasting and forecasting epidemics.

The project is in collaboration with the Department of Computer Science and Technology at the University of Cambridge and the UK Health Protection Agency (UKHSA), and aims to investigate use of machine learning for prediction of infectious diseases outbreaks. Using data from routine surveillance of respiratory infections in the first instance, the postholder will explore different approaches to blending existing ordinary differential equation-based mechanistic infectious disease models with modern deep learning approaches to develop predictive models of relevant epidemic data. Challenges include the relative scarcity of relevant training data, characteristic of epidemics, and the need to appropriately quantify uncertainty in the predictions.

The successful candidate will have a PhD in a strongly quantitative discipline, but applications from candidates close to submitting their PhD are also welcome. Familiarity with deep learning methodologies is essential, as is research experience in biomedical modelling and machine learning, statistical programming, an ability to produce high-quality academic writing, good communication skills, and an enthusiasm for collaborating with non-statistical scientists. Experience in infectious disease transmission modelling is highly advantageous. 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.

Fixed-term: The funds for this post are available for 2 years in the first instance.

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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: 24th June 2024

The interview date for the role is: To be confirmed

Please quote reference SL41765 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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