Bioinformatician / Data Engineer for the Translational Drug Response and Genomics Profiling Project(m/w/x)

Description

In this role, you will engage in cutting-edge cancer research by profiling drug sensitivity and integrating multi-omics data. Your work will involve developing computational pipelines, collaborating with scientists, and supporting innovative imaging analyses to enhance pediatric oncology outcomes.

Requirements

• •M.Sc. or Ph.D. in bioinformatics, computational biology, computer science, statistics, molecular biotechnology, or a related discipline
• •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 (e.g., Streamlit, Shiny, or Dash) is an asset
• •Background in genomics, transcriptomics, or pharmacogenomics data analysis
• •Understanding of drug screening and functional genomics data
• •Knowledge of biological data standards and reproducible research principles
• •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

Tasks

• •Conduct clinical drug sensitivity profiling
• •Identify novel biomarkers in patient-derived and cell line datasets
• •Integrate multi-omics and drug sensitivity data on a large scale
• •Develop and maintain cohort-based drug response classification applications
• •Script automated workflows for drug screening
• •Explore high-content imaging datasets
• •Develop, optimize, and standardize computational pipelines for multi-omics data processing
• •Implement and automate workflows for drug screening data analysis
• •Perform automated data quality control and hit calling
• •Classify drug sensitivity
• •Integrate genomic, transcriptomic, and pharmacologic data to identify therapeutic vulnerabilities
• •Generate user-friendly applications and dashboards for data visualization
• •Collaborate with wet-lab scientists, bioinformaticians, and clinicians on data-driven analyses
• •Contribute to AI/ML-driven high-content imaging data analysis pipelines
• •Support students and postdocs in computational and bioinformatics workflows
• •Conduct whole-genome sequencing, RNA-seq, ChIP-seq, and single-cell transcriptomics
• •Utilize multiplex confocal microscopy and live cell imaging techniques

Tools & Technologies

Benefits