BACKGROUND

RESPONSIBILITIES

• Implement and develop contemporary computational algorithms for phenotype identification, inference of biological mechanisms, and data visualization;
• Apply and assess methods on high-throughput profiling and ancillary datasets that arise both from corporate research and the public domain;
• Integrate data across multiple experimental platforms, and transfer knowledge from pre-clinical experiments to clinical trials;
• Contribute to experimental design, analysis planning, and data integration strategies in collaboration with colleagues located in the US;
• Present and report methods and results to a publishable standard, both internally and outside the company where required.

REQUIREMENTS

• A Ph.D. in computational biology or related fields from an internationally-recognized higher-education establishment;
• Experience (2+ years) in the computational analysis and interpretation of transcriptional profiling data in particular, in haematological disease or regenerative medicine research scenarios;
• Experience in the analysis of data from a wider range of relevant assay platforms, e.g. flow cytometry, would be considered advantageous;
• Experience of working within a server-based, command-line environment, and in use of the R/Bioconductor statistical programming environment;
• Track record of peer-reviewed publication and collaborative inter-disciplinary scientific research;
• Fluent verbal and written English language skills.

TERMS

LOCALE

COMPENSATION

HOW TO APPLY

DEADLINE