PhD student Machine Learning for Immunology

Core responsibilities:

• Developing robust algorithms for batch-corrected integration and summarization of scRNA-seq datasets from >1,000 patients
• Engineering human-interpretable features (cell type proportions, gene expression scores) optimized for cross-dataset stability
• Training and validating machine learning classifiers for multi-class lung disease diagnosis
• Translating scRNA-seq-derived immune signatures to spectral flow cytometry measurements
• Collaborating with clinical and experimental partners within the EC-EDI consortium

This role creates positive change by developing computational methods for early disease diagnosis and interception, translating research into clinical practice to improve patient outcomes through precision medicine approaches.

Required qualifications:

• Master's degree in a quantitative discipline: physics, mathematics, computer science, statistics, machine learning, data science, or computational biology/bioinformatics
• Strong programming skills (e.g. Python and/or R)
• Experience with machine learning methods
• Independent, structured, and detail-oriented working style
• Proficiency in English

Desirable qualifications:

• Experience analyzing high-dimensional biomedical data (e.g., omics, single-cell data)
• Familiarity with batch correction, dimensionality reduction, or multi-dataset integration methods
• Knowledge of software engineering principles (version control, testing, documentation)
• Interest in translational research and clinical application

Benefits and compensation:

• Paygrade E13 according to TVöD VKA-K (salary group mentioned but specific amounts not provided)
• Working hours can be part-time or full-time with up to 38.5 hours per week
• 30 days of paid vacation per year
• Involvement in high-profile, interdisciplinary research consortium with direct clinical impact
• Joint supervision by two leading research labs
• Extensive professional development opportunities
• Special offers in shopping, travel and sports
• Bike leasing via "JobRad" possible