Bioinformatician / Bioinformaticianess

ETH Zürich - July 27, 2025

ETH Zurich and Functional Genomics Center Zurich

The Laboratory of Regenerative and Muscle Biology at ETH Zurich, in collaboration with the Functional Genomics Center Zurich (FGCZ), offers a unique opportunity for a bioinformatician to engage in cutting-edge omics data research.

Headed by Prof. Ori Bar-Nur, the Laboratory of Regenerative and Muscle Biology (RMB) is a multidisciplinary group dedicated to translating fundamental research into therapeutically applicable treatments. The lab operates at the crossroads of molecular and cellular biology, gene- and cell-based therapies, and tissue engineering. It utilizes multiomics tools extensively in its research projects to enhance our understanding of biological processes.

The Functional Genomics Center Zurich (FGCZ) is a premier core facility of ETH Zurich and the University of Zurich, specializing in the latest omics technologies for biomolecular research and personalized medicine. The FGCZ Genome Informatics group is committed to supporting researchers with the analysis and interpretation of large-scale datasets, particularly next-generation sequencing (NGS) data. This team encompasses raw data processing, high-performance computing, statistical evaluation, interpretation, and integrated analysis. The FGCZ prides itself on maintaining a robust open-source software environment and developing state-of-the-art analytical concepts and algorithms.

Position Overview

The bioinformatician will play a pivotal role in a broad range of basic and translational research projects within the RMB lab. This position demands close collaboration with an international research team and requires a high level of motivation, scientific curiosity, and a team-oriented approach. As a member of the FGCZ Genome Informatics group, the candidate will deliver essential bioinformatics services to support a variety of ongoing projects. Responsibilities will include performing data analyses using the group's existing infrastructure and developing and implementing additional analysis workflows. There will be a particular emphasis on single-cell and spatial transcriptomics applications, so experience in these areas is highly desirable.

Qualifications

  • PhD degree in bioinformatics or a related field
  • Proficiency in NGS data analysis with strong scripting skills
  • In-depth knowledge of R/Bioconductor and/or Python
  • Practical experience with the GNU/Linux operating system
  • Genuine enthusiasm for statistical and bioinformatics data analysis
  • Strong communication skills and a collaborative mindset
  • Good understanding of biological research questions
  • Service-oriented and adaptable to the evolving field of bioinformatics
  • Advanced proficiency in English

The RMB Lab is situated in the SLA building on the Schwerzenbach Campus of ETH Zurich, a world-renowned institution. We provide an advanced work environment equipped with multiple well-resourced facilities, expert staff, and supportive colleagues, along with vibrant opportunities for innovative and dynamic projects. We offer a competitive salary and benefits package, adhering to the employment regulations of ETH Zurich.

The FGCZ boasts extensive expertise in the analysis of single-cell, spatial transcriptomics, and other NGS data types, providing an open and collaborative working environment. With our high-performance hardware and software infrastructure, we empower researchers to efficiently conduct data analysis at scale.

Apply online using the form below. Only applications matching the job profile will be considered.

For inquiries regarding the position, please reach out to Eva Skalamera (eva.skalamera@hest.ethz.ch) or Dr. Hubert Rehrauer (hubert.rehrauer@fgcz.ethz.ch). Additional information can be found on the websites of the Laboratory of Regenerative and Muscle Biology and the Functional Genomics Center Zurich.

Location : Schwerzenbach
Country : Switzerland

Application Form

Please enter your information in the following form and attach your resume (CV)

Only pdf, Word, or OpenOffice file. Maximum file size: 3 MB.