Bioinformatician (m / f / d)

Responsibilities

• Develop and implement bioinformatics workflows for single-cell RNA-seq and spatial omics data analysis.
• Optimize and apply nextflow / nf-core pipelines for data processing and analysis.
• Integrate multi-omics datasets to derive meaningful biological insights.
• Perform quality control, normalization, clustering, and trajectory inference on single-cell datasets.
• Analyze spatial transcriptomics data to study tissue architecture and cellular interactions.
• Work on high-performance computing (HPC) environments, ensuring efficient and scalable data processing.
• Develop custom scripts and software tools to enhance analytical capabilities.
• Collaborate with wet-lab scientists to interpret results and refine experimental designs.
• Maintain well-documented, reproducible, and FAIR-compliant workflows.

Qualifications

Required Qualifications

• Ph.D. or M.Sc. in Bioinformatics, Computational Biology, Data Science, or a related field.
• Strong experience in single-cell transcriptomics (scRNA-seq, scATAC-seq, etc.) and/or spatial omics analysis.
• Proficiency in R and Python for bioinformatics and statistical analysis.
• Hands-on experience with nf-core pipelines and Nextflow.
• Experience working with high-performance computing (HPC) environments and cloud-based solutions.
• Familiarity with open-source bioinformatics tools for single-cell analysis (e.g., Seurat, Scanpy, Cell Ranger, Squidpy).
• Solid understanding of machine learning approaches applied to biological data.
• Ability to work both independently and as part of a collaborative, interdisciplinary team.
• Strong problem-solving skills and attention to detail.

Preferred Qualifications

• Experience with visualization techniques for single-cell and spatial omics data.
• Experience with multi-omics integration (e.g., single-cell RNA-seq + ATAC-seq / ChIP-seq).
• Familiarity with database management and workflow automation.
• Knowledge of statistical modeling and network-based analysis.
• Contributions to open-source bioinformatics projects.

Additional Information

Benefits:

• A stimulating research environment at the intersection of computational and experimental biology.
• Engage in high-impact research projects that contribute to advances in cancer treatment.
• Opportunities for professional development, co-authorship in scientific publications, and conference participation.
• Access to cutting-edge computational infrastructure and datasets.
• Competitive salary and benefits package.

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