University of Cambridge

Job Opportunities


Research Associate*/Research Assistant (Machine Learning/Biostatistics/Statistical Epidemiology/Health Data Science) (Fixed Term)

Research Assistant - £26,715 - £30,942

Research Associate*- £32,816 - £40,322

An exciting opportunity has arisen to recruit a talented researcher interested in gaining experience in the adaption and application of cutting-edge machine learning and artificial intelligence tools to chronic disease risk prediction, screening and management using large-scale, complex datasets. It is anticipated the research will contribute to high-impact publications.

This new role lends itself to an ambitious individual with outstanding quantitative/computing/data science skills with a passion to extend their knowledge and to contribute to important health research questions. The post holder will be based in the Department of Public Health and Primary Care, University of Cambridge and will have access to exceptional world-leading large-scale studies including population databases embedded in general practice, detailed hospital electronic health records and 'multi-omics' data (e.g. proteomics, metabolomics and lipidomics, genotype array data).

The post holder will work in close conjunction with Mihaela van der Schaar, Professor of Machine Learning and Artificial Intelligence for Medicine and Dr Angela Wood, Reader in Health Data Science at the University of Cambridge, and both fellows of the Alan Turing Institute. They will also work closely with other members of the research teams.

The post holder will have a PhD in a quantitative science (eg, Mathematics, Statistics, Computing, Machine Learning) or equivalent qualifications or be in the final stages of obtaining their PhD. They will have experience of using relevant statistical and/or programming software (eg, R, Stata, Python) with strong quantitative skills and a high level of report writing and presentation skills. The post holder will also have excellent organisational and verbal skills with an ability to judge priorities and work to tight deadlines.

*Appointment at research associate is dependent on having a PhD (or equivalent experience is recognised), including those who have submitted but not received their PhD. Where a PhD has yet to be awarded or submitted appointment will initially be made at research assistant and amended to research associate when the PhD is awarded. If an individual has not submitted a PhD or is not working towards one they could be appointed as a Research Assistant if they have either a degree (degree and/or Master's) in a relevant area or equivalent experience.

The funds for this post are available until 31st October 2020.

The post-holder will be based at Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN (approx. 2 miles south of city centre)

Informal enquiries can be made to: Angela Wood ( or telephone 01223 748652.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Closing date: 26th February 2020

Interview Date: Week commencing 9th March 2020

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 RH22449 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

Apply online