Research Fellow in Cancer Genomics - Computational Biology

Institution/Company:
University College London
Location:
London, London, United Kingdom
Job Type:
  • Postdoctoral
Degree Level Required:
PhD
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Research Fellow in Cancer Genomics - Computational Biology

Context We seek a self-motivated and collaborative postdoc fellow in computational biology to join a team of bioinformaticians in the Sarcoma Genome Clinical Interpretation Partnership (100,000 genomes project). The 100,000 Genomes Project (http://www.genomicsengland.co.uk/) was set up to advance the care for patients with cancer in the NHS to improve treatment and outcomes through personalised medicine. At present, the project sequenced more than 30,000 cancers. In anticipation of this, over 30 Genomic England clinical interpretation partnerships (GeCIPs) were set up to maximise use of the data and drive the development of more advanced treatments. Each of the GeCIPs will need to perform harmonised data analysis to facilitate efficient downstream studies. One of the largest GeCIPs is the Sarcoma GeCIP (>1300 patients recruited) which is in urgent need to harmonise their data to start downstream analyses.

SARCOMA GECIP The sarcoma GECIP is multidisciplinary, constituting more than a 100 members and growing. The GECIP comprises a mix of world leading research scientists, bioinformaticians, statisticians and clinicians who all have the goal of understanding the basis of sarcoma development and to discover new ways to identify sarcoma earlier and treat it more effectively. The Genomics component of the Sarcoma GECIP is led by Dr. Peter Van Loo (Genomics) with a steering committee comprising Prof. Adrienne Flanagan (Pathology), Prof. Stephan Beck (Epigenetics) and Prof. Gareth Bond (Genetics). The post holder is expected to join a team of bioinformaticians who will develop, test and implement harmonisation and classification of the 100,000 Genomes Project data using existing benchmarked informatics pipelines for whole genome sequencing data. It is expected that as the project unfolds the post-holder will be involved in performing large-scale genomics analyses of sarcomas characterizing the landscape of driver mutations and mutational processes across sarcoma entities, and work with the team studying the evolutionary history of sarcomas. The successful applicant will have a proven track record of publications, have previous experience with NGS data analysis, be fluent in at least one of the following programming languages: R, Perl or Python, and is expected to have strong skills in the field of genomics and desirably one or more of the following: cancer biology, evolutionary biology, statistics, mathematics or machine learning. Prior experience with work on high performance clusters, and with large-scale data analysis is particularly desired. The post holder will join a team of computational biologists who will develop, test, implement and run genomics data analysis pipelines for the 100,000 Genomes Project whole-genome sequencing data and other associated ‘omics data. The position is full-time for 3 years and ideally the post holder will start at the earliest opportunity. The successful candidate will join a multidisciplinary team including Professor Adrienne Flanagan and Prof. Stephan Beck (https://www.ucl.ac.uk/cancer/research/department-cancer-biology/medical-genomics-research-group) based at UCL Cancer Institute, and Dr Peter Van Loo at the Francis Crick Institute (http://www.crick.ac.uk/peter-van-loo).

Responsibilities:

• To work within the informatics team within the Flanagan, Beck and Van Loo labs • To provide expert mathematical and statistical support • To employ novel informatics techniques based on evolutionary principles to the analysis of tumour evolution • To liaise and coordinate between various working groups involved in the sequencing of GECIP clinical samples to ensure the delivery of high quality sequence data in a time efficient manner • Ensure the necessary computational requirements are met to allow for efficient processing of the GECIP dataset • To understand cancer biology and the relevant literature sufficiently to take own ideas forward as lead author on new projects • To assist in the delivery and rapid processing of tumour data to the GECIP working groups to facilitate further research • To record all experiments in an accurate, timely and clearly presented manner, and use this to prepare data summaries and reports as and when required • To attend, and report research results at regular group and national meetings • To contribute to the dissemination of scientific results by means of writing papers for publication, and presenting orally and in poster form at national and international meetings • As duties and responsibilities change, the job description will be reviewed and amended in consultation with the post-holder • The post-holder will carry out any other duties as are within the scope, spirit and purpose of the job as requested by the line manager or Head of Department/Division • To be aware of and act upon UCL policies for: o Disciplinary procedure and Disciplinary rules o Grievance procedure o Section 7 and 8 of the Health and Safety at Work Act o Departmental Fire Guidelines o Equal Opportunities and Race Equality Policies

Qualifications:

The successful applicant will have a proven track record of publications, have previous experience with NGS data analysis, be fluent in at least one of the following programming languages: R, Perl or Python, and is expected to have strong skills in the field of genomics and desirably one or more of the following: cancer biology, evolutionary biology, statistics, mathematics or machine learning. Prior experience with work on large-scale data analysis is particularly desired. The post holder will join a team of computational biologists who will develop, test, implement and run genomics data analysis pipelines for the 100,000 Genomes Project whole-genome sequencing data and other associated ‘omics data.

It is expected that as the project unfolds the post-holder will be involved in performing large-scale genomics analyses of sarcomas characterizing the landscape of driver mutations and mutational processes across sarcoma entities, and work with the team studying the evolutionary history of sarcomas.