PhD Student in Computational Biology​/Bioinformatics

The German Cancer Research Center (DKFZ) is one of Europe’s largest cancer research centers. “Research for a life without cancer" is the mission of our world‑class scientists and all our team members.

The DKFZ is a place where the brightest minds pursue bold ideas and seek answers to pioneering scientific questions through collaboration, innovation, and exploration across many disciplines. We provide a dynamic environment which empowers excellence with state‑of‑the‑art technologies, cutting edge infrastructure, and a global scientific network.

Contribute your knowledge, vision, and dedication to create a space where scientific discovery in cancer research is transformed into benefits for human health.

Together with selected university partner sites, the DKFZ has established the German Cancer Consortium (DKTK). The alliance between the DKFZ as the core center and the university partner sites in Berlin, Dresden, Essen/Düsseldorf, Frankfurt/Mainz, Freiburg, Heidelberg, Munich, and Tübingen operates joint translation centers at the University Medical Centers of each of the selected partner sites. The DKTK contributes significantly to filling the translational gap between basic and clinical cancer research, thereby developing new strategies for personalized oncology in prevention, diagnosis, and treatment of cancer.

DKTK conducts transformative translational cancer research, educates the next generation of translation-oriented medical and clinical scientists and establishes strong pipelines towards clinical cancer research and the economy.

For the Institute of Molecular Oncology and Functional Genomics () at the DKTK partner site Munich, starting at the earliest date possible, we are seeking a PhD Student in Computational Biology/Bioinformatics.

We study the molecular basis of cancer through an integrated approach spanning genomics, molecular biology and computational biology, thereby aiming to better understand how cancers arise, spread or resist to therapy. See examples in:
Nature 2018 Feb 1;554(7690):62, Cancer Cell. 2023 Jul 10;41(7):1327;
Nature Methods. 2024 Apr;21(4):584. Nature. 2026 Feb 25. doi: 10.1038/s-2.

By developing and applying genetic technologies for high-throughput applications in cells and mice, including CRISPR or transposon tools for massively parallel screening, we create and integrate multi-dimensional data to interrogate biological systems in their full complexity. Our team brings together cancer biologists, molecular geneticists, bioinformaticians, and clinicians who collaborate closely in a creative, multidisciplinary environment.

• Genomic and screening technology development
• Computational large-scale data integration
• Cell fate transitions in development and cancer
• Molecular mechanisms of cancer evolution
• Non-coding RNA biology

We are seeking a highly motivated PhD candidate in computational biology/bioinformatics to investigate fundamental questions in cancer biology through the analysis and integration of large-scale transcriptomic, genomic, and functional genomics datasets. The successful candidate will pursue an independent research project while collaborating closely with experimental and computational researchers.

The position is 100% on-site.

• MSc degree in bioinformatics, computational biology, or a related field, or a life science degree with substantial computational biology training and programming experience
• Demonstrated hands‑on experience in computational biology through a master's thesis, internship, or research project
• Experience working in a Linux/Unix environment and familiarity with command-line tools and Bash scripting
• Experience with R and/or Python for biological data analysis
• Solid understanding of applied statistics and statistical…