Postdoctoral Researcher - Computational & Translational Analysis of Pulmonary Nodules | Postdoctoral Researcher - Computational & Translational Analysis of Pulmonary Nodules
Deutsches Krebsforschungszentrum
Job Summary
This role involves leading the integrative analysis of complex biological data to advance early lung cancer detection within the PRELUNG study at the German Cancer Research Center (DKFZ). Day-to-day, the successful candidate will perform unsupervised clustering and pattern discovery on spatial transcriptomics, genomic profiles, and radiomic features to identify biomarkers for liquid biopsies and PET tracer targets. Beyond technical analysis, the researcher acts as a scientific integrator across interdisciplinary teams and leads a unique 'Return-of-Data' work package, co-designing frameworks to communicate molecular findings back to study participants. This position is highly attractive for its blend of high-impact computational research, translational clinical application, and innovative patient engagement. Candidates will benefit from a world-class research environment, state-of-the-art infrastructure, and a comprehensive benefits package including flexible working hours and dedicated career development services.
Required Skills
Education
Master's degree and PhD in computational biology, bioinformatics, systems biology, biomedical data science, cancer biology, or a related field.
Experience
- Professional experience in omics data analysis, specifically single-cell or spatial transcriptomics
- Proven experience with modern data-analysis workflows using R or Python
- Demonstrated experience in unsupervised learning, clustering, and integrative data analysis
- Experience in translating computational findings into biological or clinical insights
- Experience in interdisciplinary leadership or public engagement with non-expert stakeholders
Languages
Additional
- Proof of immunity against measles is required per the Infection Protection Act (IfSG). The position is initially limited to 2 years with a possibility of extension.
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