Salary in the region of £36,737 - £44,451 (dependent on experience) plus excellent benefits
Fixed term for 5 years
An exciting statistical analysis and development opportunity has become available within the Cancer, Ageing and Somatic Mutation Group (CASM). The successful candidate will be embedded in a large multidisciplinary team and will be tasked with further developing our cancer analysis algorithms specifically for cancer predisposition and cancer evolution.
The role involves working closely with scientific/IT staff within CASM to develop novel analysis strategies and actively contribute to the statistical modelling and data analysis of this important study. In addition, the role will also involve improving existing algorithms and developing new software when required as well as analysing whole genome sequencing and single cell data.
The position would suit a Bioinformatician/Statistician who enjoys developing algorithms and statistical modelling to analyse complex NGS biological data sets. We are looking for an individual who enjoys working in a multi-disciplinary team environment, to help solve complex IT issues, which will ultimately aid our analysis of cancer related datasets.
Degree in Bioinformatics, Mathematics, Statistics or Computer Science with a scientific background.
Software development skills (using Perl and/or Python)
Experience of bioinformatics and familiarity with genome data
Evidence of proficiency in Perl programming or another modern computer language
Strong UNIX/LINUX skills
Experience of working with biological analysis pipelines on multi-node compute clusters
Proficient in statistical analysis of genome-wide datasets
Previous scientific publications
Enjoy working as part of a team
PhD in a bioinformatics or mathematics subject
Experience in single cell analysis
LSF or Open Grid scheduling software
R and/or Matlab programming experience
Experience of workflow management IT systems
Experience working, developing and compiling software tools in a UNIX/LINUX environment.
Background in cancer genetics
Evidence of academic excellence
Please apply directly via our website portal;- https://jobs.sanger.ac.uk/wd/plsql/wd_portal.show_job?p_web_site_id=1764...
Please include a covering letter and CV with your application.