Research Software Engineer for Computational Mass Spectrometry

ETH Zurich seeks a Research Software Engineer to develop bioinformatics pipelines for computational mass spectrometry data analysis in Zürich.

This position supports researchers at the FGCZ by managing raw data processing, high-performance computing, and statistical evaluation. The role is central to integrating data into management systems and ensuring that all analytical workflows remain reproducible and accessible.

Responsibilities

• Maintain current and build new pipelines for processing and analyzing mass spectrometry data.
• Utilize informatics and data science methods to guarantee the reproducibility of analytical results.
• Provide back-office and user-desk support to collaborators, assisting with data interpretation and bioinformatics project execution.

Requirements

• Hold a Master’s degree in a relevant discipline such as computer science, statistics, or biology.
• Demonstrate proficiency in Microsoft Windows and Linux environments, including command-line usage.
• Possess practical experience with at least one programming language (e.g., C++, C#, Java, Python) and version control tools like Git.
• Have advanced English language skills, as this is the primary working language of the center.
• Work effectively both independently and as part of a team, interacting well with research and technical staff.

Nice to have

• Experience managing and analyzing large-scale datasets, especially omics-related data.
• Background in bioinformatics, with a preference for mass spectrometry expertise.
• Knowledge in imaging, spatial, or cross-omics fields.
• Proven history of writing and maintaining code.
• Familiarity with R/Bioconductor and client-side web programming.
• Experience in UI/UX design for scientific data visualization interfaces.
• Experience with virtualization tools such as Docker or Apptainer.
• Experience with resource management software like Slurm.

About the company

The team at ETH Zurich maintains a portfolio of commercial and open-source applications that operate on their infrastructure. They are dedicated to establishing novel data processing and analysis pipelines to support scientific research.

• The team maintains a portfolio of commercial and open-source applications operating on their infrastructure.
• The team establishes novel data processing and analysis pipelines.