Bioinformatician / Data Engineer for the Translational Drug Response and Genomics Profiling Project

Reference number: 2025-0332

• Heidelberg
• Full-time
• Clinical Cooperation Unit “Pediatric Oncology”

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.

About the Project:

Drug Sensitivity Profiling & Multi-Omics Integration Clinical drug sensitivity profiling and identification of novel biomarkers in both patient-derived and cell line datasets. Responsibilities include large-scale integration of multi-omics and drug sensitivity data, development and maintenance of cohort-based drug response classification applications, and scripting for automated drug screening workflows. The ultimate goal is to identify novel therapeutic targets and improve diagnosis, prevention, and treatment outcomes in pediatric oncology
The project also involves exploration of high-content imaging datasets; Therefore, experience or interest in AI-based image analysis would be advantageous.

The position is jointly hosted by the groups “Translational Genomics” led by Dr. Robert J. Autry and “Functional Pediatric Precision Oncology” led by Prof. Dr. Ina Oehme.

What's special about this position:

• An interdisciplinary research environment within one of Europe's leading pediatric cancer research centers
• Access to large-scale genomics and pharmacological datasets
• Collaborative supervision and mentorship by both the Autry and Oehme groups
• Opportunity to contribute to clinically translatable discoveries in pediatric oncology

Your tasks:

• Develop, optimize, and standardize computational pipelines for multi-omics data processing (eg, mutation calling, RNA-seq, methylation, and epigenomic profiling)
• Implement, automate, and maintain workflows for drug screening data analysis , including automated data quality control, hit calling, and sensitivity classification
• Integrate genomic, transcriptomic, and pharmacologic data across multiple platforms to identify therapeutic vulnerabilities and predictive biomarkers
• Generate user-friendly applications and dashboards for data visualization and exploration
• Collaborate closely with wet-lab scientists, bioinformaticians, and physicians to design data-driven analyzes for translational studies
• Contribute to AI/ML-driven high-content imaging data analysis pipelines for assessing drug effects on cancer cells
• Constant support of students and postdocs in basic computational and bioinformatics workflows

Genomic and functional screening approaches include, but are not limited to:
Whole-genome sequencing, RNA-seq, ChIP-seq, single-cell and spatial transcriptomics, and large-scale drug response assays ; imaging approaches include multiplex confocal microscopy and live cell imaging

Your profile:

• Education : M.Sc. or Ph.D. in bioinformatics, computational biology, computer science, statistics, molecular biotechnology, or a related discipline
• Technical Skills:
• • Proven experience with Linux/Unix, Python, R, and Bash scripting
  • Strong background in bioinformatics workflows, multi-omics integration , and/or machine learning
  • Experience with high-performance computing environments is beneficial
  • Familiarity with AI-based image analysis and data visualization frameworks (eg, Streamlit, Shiny, or Dash) is an asset
• Scientific Expertise:
• • ground in genetics, transcriptomics, or pharmacogenomics data analysis
  • Understanding of drug screening and functional genomics data
  • Knowledge of biological data standards and reproducible research principles
• Soft Skills:
• • Strong communication skills and ability to present and document findings
  • Collaborative, supportive, curiosity-driven, and organized, with attention to detail
  • Fluent in English (German not required)
  • Ability to work both independently and as part of a multidisciplinary team

Application Process:

Interested candidates should submit the following documents via our online application tool:

• Curriculum vitae
• Master's and/or doctoral degree certificates
• Letter of motivation
• Contact information for two references

We Offer

Are you interested?

Then become part of the DKFZ and join us in contributing to a life without cancer!