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DKFZ in Munich seeks a highly motivated PhD candidate in computational biology/bioinformatics to analyze large-scale transcriptomic and genomic datasets. You will pursue an independent project while collaborating with experimental and computational teams in a vibrant, translational cancer research environment.
The position is 100% on-site, with access to international networks and a strong mentoring program through the DKFZ International PhD Program.
Reference number: 2026-0194
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. 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/s41586-026-10187-2.
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.
Our open research areas include:
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.
Then become part of the DKFZ and join us in contributing to a life without cancer!
Contact: Prof. Dr.RolandRad
Phone:+49 (0)89 4140 4374
Duration: The position is initially limited to 3 years.
Application Deadline: October 8, 2026
We are convinced that an innovative research and working environment thrives on the diversity of its employees. Therefore, we welcome applications from talented people, regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical ability, religion and age. People with severe disabilities are given preference if they have the same aptitude.
Notice: We are subject to the regulations of the Infection Protection Act (IfSG). Therefore, all our employees must provide proof of immunity against measles.