Required Qualifications

• Master or Ph.D. in Biostatistics, Data Science, Machine Learning or Bioinformatics
• Experience with genomics data including compositional microbiome data such as whole-genome and 16S rRNA sequencing analysis and sc RNA seq data analysis
• Proficiency in exploratory data analysis (EDA) and a solid understanding of machine learning algorithms
• Expertise in multiple programming languages, such as Python and R, with experience working in Linux-based environments and HPCs

Preferred Skills

• Familiarity with explainable AI tools (e.g., LIME or SHAP) for interpreting machine learning models
• Experience with multi-omics data integration
• Strong problem-solving abilities and a proven track record of effective collaboration within interdisciplinary teams
• Proficiency in Englisch (written and communication)

The Lab of Translational Microbiome Research, led by Dr. C. Stein-Thöringer, is part of the Cluster of Excellence “Controlling Microbes to Fight Infections” (CMFI) at the University of Tübingen. Our lab investigates how gut microbes, pathogens, the immune system and environmental factors shape cancer development, therapy outcomes and susceptibility to infections. We are offering a research position in data science as part of a collaborative research project examining the role of the microbiome in cancer development and therapy. This project employs a multi-omics approach, integrating microbiome data, metabolomics, immune phenotypes and clinical records to uncover the relationships between microbes and their host in the context of cancer or cancer therapies. The research will be conducted at the state-of-the-art M3 Institute at the University of Tübingen.