BACKGROUND

RESPONSIBILITIES

• Working as an CompBio Expert within the Computational Biology Group together with members of the Therapeutic Area Partner function and members of the Computational Biology Core function
• Establishing and developing new analysis strategies for RNA-Seq, single cell RNA-Seq and other NGS approaches
• Overseeing and contributing to the development of automated standard analysis pipelines, automation of interactions between infrastructure components, or requirements analyses for such systems. Contributing to BI's global computational biology infrastructure in collaborations with bioinformaticians and members of IT and external partners in international teams
• Acting as the key interface to the NGS lab within the Computational Biology group and play a driving role in the definition of experimental design strategies and coordinate the implementation and development of the LIMS. Together with the NGS lab developing outsourcing strategies
• Carrying out data analyses to generate and test hypotheses in the context of new therapeutic concepts in collaboration with other members of the Computational Biology group or scientists from BI's Therapeutic Areas for Drug Discovery (Cardiometabolic Research, Central Nervous System Research, Inflammation & Respiratory Research, Immune Modulation & Research Beyond Borders). Supporting others and driving projects as the responsible computational biologist
• Contributing to projects during all phases from experimental design to downstream analysis as the computational biology specialist in interdisciplinary teams

REQUIREMENTS

• PhD degree or equivalent qualification in Computational Biology or related fields several years of post-PhD experience with a focus on GWAS
• Excellent knowledge and a broad spectrum in bioinformatics and computational biology with a focus on topics related to RNA-Seq, single cell RNA-Seq and other NGS applications. (Ideally analyzed from initial QC to downstream a large number of different RNA-Seq projects, and hands-on experience with scRNA-Seq data from multiple platforms. In addition you have a good overview of recent developments in terms of NGS instruments and protocols. Ideally you have collaborated closely with genomics teams and dealt with LIMS as well).
• Your solid background in statistics and experimental design allows you to define the way forward also for complex questions.
• Several years of experience in R/Bioconductor or Python and at least one additional programming language. You have robust coding skills, experience with version control systems (e.g. git) and constantly strive for well documented and reproducible analyses. In addition you are familiar with Linux, local and cloud-based HPC environments and have experience with queuing systems and modern pipelining systems (e.g. CWL, bpipe etc).
• Experience with other type of omics data, network biology or machine learning is an additional asset.
• Previously demonstrated that you can apply your skills to turn large datasets into relevant insight in concrete biological and disease related topics in interdisciplinary collaborations.
• Fluency in English both in writing and in speaking will enable you to act in an international working environment.
• You are characterized by a focused working style, flexibility as well as innovative thinking, and problem solving and analytical skills.
• You are a reliable team player with excellent organization and communication skills, and with a high degree of motivation.

HOW TO APPLY