The appointment will be on UCL Grade 7.

The remit of this post is to undertake computational and statistical analyses on the genomic data (whole genome and targeted sequencing) from sizeable cohorts of subtypes of sarcoma. The results will then be developed using next generation sequencing technologies for diagnostic, predictive and prognostic biomarkers in the clinic. Some of the data will be accessed from the International Cancer Genome Consortium patient cohorts generated from studies co-led by Prof Flanagan. There will be opportunities to work in the new eMedLab in order to integrate data sets (https://www.ucl.ac.uk/news/news-articles/0214/06022104-UCL-medical-bioinformatics-grant ). In addition 500 sarcomas from across the UK will undergo whole genome sequencing as part of the 100,000 genomes project and the establishment of a Sarcoma GeCIP will provide exciting opportunities to the successful applicant.

The post holder will work closely with Prof. Flanagan, Dr Javier Herrero (Head of the Computational Cancer Genomics Group), Dr Pillay (clinician scientist), Dr Gupta (senior post-doctoral scientist) and other clinical histopathologists. The work will be undertaken primarily at UCL, the research base for the Flanagan and Herrero groups ( http://www.ucl.ac.uk/cancer/pathology/geneticssarcoma ) ( www.ucl.ac.uk/cancer/blic ), and there will be close interactions with the pathology unit at the Royal National Orthopaedic Hospital (diagnostic laboratory https://www.rnoh.nhs.uk/clinical-services/cellular-and-molecular-pathology. Some time may be spent accessing databases at RNOH.

The post is funded for 2 years in the first instance.

The ideal candidate will have a MSc in computational biology and a strong background in NGS-based genome and some experience in transcriptome analysis. Experience with cancer genomics data will be beneficial. You will be responsible to lead such analyses and develop the required pipelines. You will be collaborating with other researchers of the institute in the interpretation of the experimental results.

UCL Reference: 1479758

Applicants should apply online. Please click on the ‘Apply’ button below.

For enquiries regarding the application process please contact e-mail CI.Vacancies@ucl.ac.uk

Interview Date: To be confirmed

We particularly welcome applications from black and minority ethnic candidates as they are under-represented within UCL at this level.