Research Associate (Fixed Term) x 2

University of Cambridge - Cancer Research UK Cambridge Institute

The Markowetz lab at the Cancer Research UK Cambridge Institute is looking for two postdoctoral researchers to work on inferring cellular networks from single cell RNA-seq profiles after CRISPR perturbations.

Background - Several recent high-impact papers introduced experimental techniques for single-cell based genetic screens to understand gene function and cellular signalling pathways. These techniques combine single-cell RNA sequencing (scRNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)- based perturbations to massively scale up the resolution and scope of previous genetic screening technologies. The technology is flexible and will most likely soon be used very widely across molecular biology. As these technologies are brand-new, tailored computational analysis of these data is lagging behind experimental advances.

Goals - We will develop a machine learning approach to efficiently analyse scRNA-seq CRISPR screens and infer gene interaction networks and pathways of information flow in the cell. Our approach is based on an established machine learning method called Nested Effect Models (NEMs), which has been pioneered by us. Over the last twelve years NEMs have been refined, extended, and applied by a world-wide community of independent groups, and now there exists a substantial body of methodological developments and experience in applications, which we will leverage for the analysis of scRNAseq CRISPR screens.

Collaborations - We will collaborate with Dr Sarah Teichmann's lab at the Sanger Institute and Dr Christoph Bock's lab at CEMM in Vienna. Working with these leading developers of scRNA-seq CRISPR screens, we will use our methodological advances to optimise the study design of future screens and showcase the power of our approach in collaborative case studies.

Funding - This project is funded by the BBSRC

Skills needed - The successful applicants should have data analysis skills and experience with genomic data. One postdoc position requires a good quantitative background in statistics or algorithmics for method development; the second position will focus more on the application of methods to our collaborators' data sets

Fixed-term: The funds for this post are available until 31 March 2020 in the first instance with the possibility of a further 1 year extension.

Once an offer of employment has been accepted, the successful candidate will be required to undergo a basic disclosure (criminal records check) check and a security check.

To apply online for this vacancy and to view further information about the role, please visit: This will take you to the role on the University’s Job Opportunities pages. There you will need to click on the 'Apply online' button and register an account with the University's Web Recruitment System (if you have not already) and log in before completing the online application form.

Please ensure that you upload a covering letter 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.

The closing date for applications is Friday 9th February 2018 and interviews yet to be confirmed.

Please quote reference SW14405 on your application and in any correspondence about this vacancy.

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