„Research for a life without cancer“ is our mission at the German Cancer Research Center. We investigate how cancer develops, identify cancer risk factors and look for new cancer prevention strategies. We develop new methods with which tumors can be diagnosed more precisely and cancer patients can be treated more successfully. Every contribution counts – whether in research, administration or infrastructure. This is what makes our daily work so meaningful and exciting.
The Division of Scientific Board is seeking as soon as possible a Division Head (W3) in Pediatric Cancer Drug Discovery.
Reference number: 2025-0078
The German Cancer Research Center (DKFZ) welcomes applications for a tenured position as Division Head in Pediatric Cancer Drug Discovery. This position offers a unique opportunity to lead a pioneering research program aimed at developing innovative therapies for childhood cancers, which present distinct biological challenges and limited commercial incentives due to small patient populations and thus market sizes. Academic drug discovery thereby is key to address this unmet medical need and advance treatment options for children with cancer.
The DKFZ division will be embedded within the Hopp Children's Cancer Center Heidelberg (KiTZ, https://www.kitz-heidelberg.de/en/ ), the leading pediatric oncology research center in Germany that integrates cutting-edge basic, translational, and clinical research and will be part of one of the DKFZ's research programs.
The new division will conduct cutting-edge, translational drug discovery research, with potential focus areas including:
* Functional and preclinical validation of targets associated with pediatric cancers including targets that are currently considered undruggable (e.g. fusion oncoproteins that are commonly driving pediatric cancers)
* Development and implementation of the drug discovery strategy most suitable for the target(s) concerned, involving the development of small molecule inhibitors (incl. PROTACs & glue-like degraders) or antibodies and including potential delivery needs (e.g. CNS penetration).
* Utilization of AI-driven methods and advanced predictive models for target identification, drug discovery, response prediction, and leveraging computational tools and large-scale omics and structural data to prioritize and optimize therapeutic candidates.
* Screening campaigns based on computational in silico predictions and hit- and lead optimization programs for pediatric cancers
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