Postdoctoral Training Fellow in Machine-learning of Health Records

The Francis Crick Institute

The Francis Crick Institute (the Crick) is a research institute dedicated to discovering the fundamental biology underlying human health, with the aim of improving the diagnosis, treatment and prevention of human disease.

SUMMARY

We seek a talented, motivated postdoc to join Nick Luscombe’s Laboratory of Bioinformatics & Computational Biology (www.luscombelab.org). The postdoc will apply state-of-the-art machine-learning methods to genomic and health record data, so developing new approaches to prevent, diagnose and treat human diseases. The lab is happy, international and interactive; the ~12 students and postdocs are recruited worldwide and come from a range of academic backgrounds including biology, physics and mathematics. Based in central London, the postdoc collaborate with the neighbouring UCL Hospital, Farr Institute and Alan Turing Institute. Our postdocs have an excellent track record of moving onto PI positions.

PROJECT SCOPE/ DESCRIPTION

We integrate disparate genomic and, recently, electronic health record data to study important biological phenomena from gene regulation to human health. The postdoc will develop machine-learning approaches to examine these complex data; ongoing projects include: (i) modelling competition between DNA-binding proteins to understand how genes are targeted for correct expression; (ii) building prognostic models from electronic health records to predict the likelihood of cardiac diseases. Recent successes include studies of: DNA organisation and gene regulation (Mifsud, Nature Genetics 2015); protein-RNA interactions and the impact on RNA-processing (Sugimoto, Nature 2015; Zarnack, Cell 2013); and risk-management during genome evolution (Martincorena, Nature 2012).

Please note: all offers of employment are subject to successful security screening and continuous eligibility to work in the United Kingdom.

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London