Research Associate (Bioinformatics) – Miller lab (Fixed Term)
Cancer Research UK Cambridge Institute
How do cancers create a pro-tumourigenic microenvironment? In the Miller Lab at the CRUK Cambridge Institute we are addressing this question using an array of technologies ranging from informatic analysis of human clinical data to proteomic and genomic analysis of tumour microenvironment models of the tumour microenvironment (Gauthier et al 2013 Nat Methods, Gauthier et al 2016 NAR, Jimenez-Sanchez et al 2017 Cell, Jimenez-Sanchez et al 2018 BioRxiv, Gill et al 2018 BioRxiv, http://www.miller-lab.org/ ).
We are now looking to hire a dedicated Research Associate to join a small team of scientists studying cell-cell communication within the tumour microenvironment. This three year position will explore the tumour immune microenvironment of ovarian cancer through recently acquired funding from the Target Ovarian Cancer Foundation: https://www.targetovariancancer.org.uk/news/unlocking-power-immune-system
Following our recent in-depth analysis of a patient case of ovarian cancer (Jimenez-Sanchez et al 2017, Cell), we will combine immunogenomics and bioinformatics analysis to: 1) assess the extent of immune heterogeneity in ovarian cancer using large patient cohorts, and 2) understand how chemotherapy shapes the tumour immune microenvironment with the ultimate aim of unlocking the power of the immune system for improved therapies for ovarian cancer.
You will develop an independent research project to investigate how ovarian cancer cells escape immune control in ovarian cancer by systematic, computational analysis of human clinical samples. You will apply and optimise multiple analysis tools used in the lab as well as novel tools, which could include somatic mutation calling, tumour clonality analysis, tumour purity estimation, HLA allele inference, neoantigen prediction, single-sample gene set enrichment analysis for immune cell deconvolution, TCR sequencing analysis, and/or single cell analysis with multiparameter immuno-histofluorence or imaging mass cytrometry. You have experience in quantitative modelling of biological data and in advanced statistical approaches such as generalised linear modelling, permutation-based null modelling, and/or machine learning. Having demonstrated ability to develop data-driven models based on high dimensional data from either mass cytometry, imaging, genomics or proteomics is essential. You will interact with wet and dry-lab members in a highly collaborative laboratory and contribute to the design and development of on-going research projects of other members of the group.
You should have a PhD, ideally within computational biology, systems biology, or bioinformatics. You will have demonstrated creative and independent work and published within the field of cancer research.
Fixed-term: The funds for this post are available for 3 years in the first instance.
Once an offer of employment has been accepted, the successful candidate will be required to undergo a security check.
To apply online for this vacancy and to view further information about the role, please visit:
The closing date is 6 February 2019, with the interview date to be confirmed.
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.
Please quote reference SW17817 on your application and in any correspondence about this vacancy.
Closing date: 06 February 2019
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