Bioinformatician (m/f) 80-100%

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

Kinderspital Zürich as an employer

Kinderspital Zürich is the largest university children's hospital in Switzerland with about 2,500 employees, and is one of the leading centres for paediatric and youth medicine in Europe. Although the hospital may be big, it's the little ones that count: up to 100,000 patients are cared for each year across 47 faculties, where we do everything in our power to ensure their well being. 'Kispi' not only offers cutting-edge devices and the highest quality of care, but also a good sense of interpersonal issues. Alongside its comprehensive range of paediatric medicine and surgery facilities, the children's hospital also offers a unique rehabilitation centre and a research centre.

Leal Oburoglu, Ph.D.
Research Assistant

• 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.