BACKGROUND

RESPONSIBILITIES

• Lead and deliver key bioinformatics activities to support:
  
  • 'Oncotrack' Innovative Medicines Initiative (IMI) consortium, with critical alignment to the informatics collaborators at Max Planck and Alacris (Berlin).
  • Cross platform 'omic profiling analysis (inc. next generation sequencing) of clinical and animal model data, in particular RNA-Seq, MeDIP-Seq, Exome and WGS and protein arrays.
  • Essential NGS capability build focused on extracting biological value and interpretation.
  • Integrative informatics solutions to address multi-biomarker platform deliveries.
  • Reactive toolkit build to enhance access to 'omic data by science teams including involvement in the tranSMART translational informatics platform.
• Work collaboratively with informatics specialists to deliver scientific information platforms, processes, tools and techniques to solve scientific problems.
• Build expertise in and develop novel statistical/computational methods and software tools for analyzing next-generation sequencing and high-throughput functional genomic data, including RNA-seq, DNA-seq, and large volumes of data in public repositories such as TCGA/GEO/ICGC.
• Publish in peer-reviewed journals and present at conferences/scientific meetings.

REQUIREMENTS

• PhD level in a computational biology, bioinformatics, computer science or equivalent subject
• Advanced expertise in the application, analysis and interpretation of sequencing data e.g. RNA-Seq, DNA-Seq, Meth-Seq, Exome sequencing
• Familiarity with Unix/Linux operating systems
• Highly competent in one or more of Perl, Python, Ruby, Java, C++, R programming languages
• Excellent communication and facilitation skills including delivery of appropriate formal or informal presentations to different scientific audiences
• Ability to work effectively within a team to achieve collaboration objectives by contributing to discussions and disseminating knowledge and information
• Passion for application of bioinformatics to drug discovery and delivering therapies for patients.
• Good track record of publishing scientific research

PREFERENCES

• Interdisciplinary background in bioinformatics/computational biology and cancer genomics
• Advanced knowledge of statistical and machine learning methods
• Bachelors degree or MSc in a Life Science, Computer Science or equivalent experience
• Disease area and/or domain knowledge in Biological Sciences or similar
• Experience in "big data" analysis including integration of diverse data types such as mutation, copy number and expression

TERMS

LOCALE

COMPENSATION

HOW TO APPLY

DEADLINE