The Blundell lab at the University of Cambridge is seeking a candidate for a new postdoctoral position as a Research Associate in computational biology: exploiting immune repertoire dynamics for early cancer detection. We are an interdisciplinary group focused on applying mathematical, evolutionary, and, statistical approaches to understand the somatic evolution occurring in our tissues, how this impacts cancer risk and how we can use this develop early diagnosis tests. We are particularly interested in exploiting deep sequencing data sets from longitudinal blood samples collected over multiple decades from the same individuals to study dynamics of both tumors and the body's immune response to tumors.
This project will involve the statistical and computational analysis of quantitative lineage tracking data of millions of T-cell clones in the peripheral blood of hundreds of people with and without cancer over a period of 20-years from an existing "fossil record" of frozen blood samples. The central goal of the project is to determine whether certain T-cell receptor sequences (those that recognize the tumour) produce a measurable signal as cancer develops, and thus whether immune-repertoire tracking could be used as a sensitive detector of early cancer. T-cells are immune cells that undergo somatic recombination in the thymus to produce a large diversity (10 million) of clones with different TCR sequences that code for receptors that recognize foreign antigens. Working with collaborators Harlan Robins (Fred Hutch and Adaptive Biotechnologies) and Doug Easton (Cambridge) we will probe the dynamics of these T-cell clones down to very low frequencies and across many years of life to determine whether cancer-specific signals exist and how predictive of early cancer onset they are.
The successful candidate would have expertise in quantitative and computational modelling and ideally a background in a STEM science. They should have a passion for applying quantitative techniques to understanding biological problems and be proficient with at least one of: Python, R, Matlab, C++, Fortran. Experience with large genome-scale datasets and/or machine learning is a plus.
The Blundell lab is part of the Department of Oncology at the University of Cambridge and the Early Detection Programme of the CRUK Cambridge Centre. Situated on Cambridge Biomedical Research Campus, with close ties to Addenbrooke's Hospital and a host of biotech companies, our location affords our members access to human tissue samples, state of the art sequencing facilities, and the opportunity to forge collaborations with world class physicists, engineers, biologists and clinicians in Cambridge.
Informal enquiries should be directed to Jamie Blundell via e-mail: email@example.com.
Fixed-term: The funds for this post are available for 2 years in the first instance.
Once an offer of employment has been accepted, the successful candidate will be required to undergo a health assessment and a security check.
To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.
Please ensure that you upload a covering letter, statement of interest and CV in the Upload section of the online application. 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.
Closing date for applications is the 10th June 2018, with interviews yet to be confirmed by the department.
Please quote reference RD15482 on your application and in any correspondence about this vacancy.
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