An exciting opportunity has arisen for a key analytical role in the Department of Public Health and Primary Care, University of Cambridge, funded by Cancer Research UK. A key responsibility of the post holder will be to utilise population-wide electronic health records to investigate the generalisability and transportability of models for the early detection and diagnosis of cancer.

The post-holder will contribute to the development and application of statistical and machine learning approaches to adapt models for the early detection and diagnosis of cancer for clinical use in real world settings. The research will have translational and methodological impact.

The preferred candidate will have a PhD (or equivalent) in Health Data Informatics, Data Science, Computer Science, Mathematics, Statistics, Operational Research or other related quantitative subjects. Otherwise, if the candidate can demonstrate an outstanding fit to all the other criteria, a good Masters degree in one of the relevant fields will also be considered. They will have strong computational skills in at least one of R, Python, SQL or Pyspark; experience of working with electronic health records; and a good understanding of and experience in statistics and machine learning.

This position is full time and available immediately. The funding for this post is available for 12 months from commencement in post.

Location - University of Cambridge Heart and Lung Research Institute, Biomedical Campus, Papworth Road, Trumpington, Cambridge CB2 0BB (approx 2 miles south of city centre).

The University is developing a hybrid working policy so we would welcome applications on a flexible or hybrid basis.

Informal enquiries can be made via email to Dr Samantha Ip (hyi20@medschl.cam.ac.uk)

Closing date: 12th February 2023

Interview Date: To be confirmed

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

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 additional documents that have not been requested, we will not be able to consider these as part of your application.

Please include details of your referees, including e-mail address and phone number, one of which must be your most recent line manager.

Please quote reference RH35070 on your application and in any correspondence about this vacancy.

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