Bioinformatician (m/f) 80-100% - in translational research teams in pediatric cancer

in translational research teams in pediatric cancer

Your responsibilities

• As a key computational partner within a collaborative research environment, you will provide bioinformatics expertise across research groups, developing reproducible analysis workflows, integrating diverse omics datasets, and translating complex data into meaningful biological insights.
• In this role, analyzing high-throughput sequencing data (WGS, WES, RNA-seq, single-cell RNA-seq, and ATAC-seq), as well as metabolomic and proteomic datasets, will be a central responsibility.
• Your expertise will be essential for developing, optimizing, and maintaining robust and reproducible computational pipelines for variant calling, differential expression analysis, and related bioinformatics workflows.
• A key aspect of your work will be the integration of public cancer genomics datasets with internal and external experimental data to support innovative research projects.
• Working closely with researchers across disciplines, you will provide statistical support, create insightful data visualizations, and contribute to the biological interpretation of complex datasets.
• Supporting the laboratory's computational infrastructure, you will maintain code repositories, improve workflow documentation, and ensure effective data storage management.
• Your contributions will extend to the preparation of scientific manuscripts, grant applications, and research progress reports.

Your profile

• How to apply: Submit a single PDF containing a cover letter (max 2 pages), your CV, publication list and contact details for two references
• Degree: Master's or PhD in Bioinformatics, Computational Biology, Computer Science, or a related analytical field
• Programming & computing: Proficiency in Python or R, shell scripting (Bash) in a Linux/Unix environment, and experience working with High-Performance Computing (HPC) or cloud environments (AWS/GCP)
• NGS & workflows: Proven track record in analyzing Next-Generation Sequencing (NGS) data (experience with single-cell analysis is a plus) and familiarity with workflow management systems such as Nextflow and Snakemake
• Language: Excellent written and spoken English communication skills
• Domain: Prior research background in hemato-oncology, immunology, or cancer metabolism
• Single-cell: Hands-on experience with single-cell multi-omics data analysis (Seurat, Scanpy)
• Mass spectrometry: Experience in metabolomics or lipidomics data analysis
• Statistics: Strong foundation in biostatistics and machine learning applications in oncology

Your salary ##

The exact salary will depend on your qualifications and professional experience. Your salary will be established in accordance with our salary guidelines during the selection process. Applicants who do not yet possess the necessary skills and experience may in some cases be offered a lower pay grade. In many cases, supplementary pay will be offered for irregular working hours. Further salary development will depend on your performance and the financial ability of the Eleonorenstiftung.

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Contact ###

Leal Oburoglu, Ph.D.
Research Assistant

Onkologie

Yigit Baskan
HR Business Partner
\+41 44 249 23 03 Apply now

Your start with us

Ready to make an impact? We look forward to hearing from you.

Your location ###

Lenggstrasse 30
8008 Zürich

Open Google Maps

Steinwiesstrasse 75, 8032 Zürich