Genomics Data Scientist (897396-GBA)
- Experience Level
- Experienced (non-manager)
Our client, an innovative and dynamic bio-pharmaceutical company headquartered in Switzerland, covering multiple therapeutic areas, committed into delivering products on the market over the next 5 years, is looking a Genomics Data Scientist for a permanent position based in Basel area.
The ideal candidate should have a PhD in Bioinformatics or Computational Biology, 5+ years postdoctoral experience applying advanced types of data analysis, experience working with multi-modal single cell and data, and proficiency using R, Python, Java and/or Shell programming languages.
- Driving the exploration and validation of novel drug targets and/or biomarkers
- Continuous improvement of analytical procedures; evaluation, validation and implementation of new tools and methodologies
- Developing and constantly innovating the Translational Biomarker strategy
- Documenting, reporting, and communicating results to the teams
- Publishing, presenting, and discussing scientific results at international meetings; Be a representative of the Biomarker strategy towards an international expert audience
- Developing standardized NGS analysis pipelines and workflows: Data storage, data management, data retrieval with queries, data visualization and biological data interpretation based on the biological questions
- Effectively communicate project context and results with team members in the Translational Biomarkers, Biology and Pharmacology groups
Qualifications and Experience:
- Relevant Swiss working/residency permit or Swiss/EU-Citizenship required.
- A PhD in bioinformatics or any other relevant life sciences discipline with demonstrated experience in complex data analysis of omics data sets
- Minimally 5 years postdoctoral experience of applying advanced types of data analysis, proven by a strong publication record or 2 years Industry experience
- Strong experience with the processing and biological interpretation of sequencing data from different single cell technologies, including methods for full-length (e.g. SmartSeq2) and UMI-based (e.g. 10X Genomics’ Chromium, Drop-seq, InDrops) profiling. Experience in working with CyTOF data would be an asset
- Demonstrated ability to test and/or develop new computational tools to draw relevant biological insight from bulk and single cell transcriptomic data with respect to target validation, compound mode of action and translatable biomarkers
- Expert knowledge in omics information resources and more advanced pathway / biological network analysis
- Background in computational analysis, experienced in statistical analysis with good scripting and programming skills (e.g. shell, R/bioconductor, Python, Java)
- Full professional proficiency in English.
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