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Bioinformatician​/Data Engineer

in 69115, Heidelberg, Baden-Württemberg, Deutschland
Unternehmen: dkfz. Deutsches Krebsforschungszentrum
Vollzeit position
Verfasst am 2026-01-20
Berufliche Spezialisierung:
  • Forschung/Entwicklung
    Klinische Forschung, Datenwissenschaftler
Gehalts-/Lohnspanne oder Branchenbenchmark: 40000 - 60000 EUR pro Jahr EUR 40000.00 60000.00 YEAR
Stellenbeschreibung
Stellenbezeichnung: Bioinformatician / Data Engineer

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

Reference number:

  • 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.

The Hopp Children's Cancer Center Heidelberg (KiTZ) is a joint institution of the DKFZ, Heidelberg University Hospital (UKHD), and the University of Heidelberg (UniHD). As a treatment and research center for oncological and hematological diseases in children and adolescents, KiTZ is committed to exploring the biology of childhood cancer and closely linking promising research approaches with patient care – from diagnosis to treatment and aftercare.

The Clinical Cooperation Unit "Pediatric Oncology" and the Division of Pediatric Neurooncology at the German Cancer Research Center and the Hopp Children’s Cancer Center Heidelberg are jointlyseeking a

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 (e.g., 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 clinicians to design data‑driven analyses 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…
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