Machine Learning (PI: Theis) Development and application of machine learning techniques for the analysis of scRNA-seq data/ Artificial intelligence in biomedical data science
Quantitative Single Cell Dynamics (PI: Marr) Biomedical image computing/ Data driven mathematical modeling
Genetic and Epigenetic Gene Regulation (PI:Heinig) Causal inference using polygenic risk scores and gene expression
Optimization of Patient Treatment (PI: Ahmidi) Investigating patients conditions and quality of their treatments in hospital/ Developing visualization tools for patients treatments in hospitals
Physics and data-based modeling of cellular decision making (PI: Scialdone) Developing computational tools for single-cell RNA-seq data analysis/ Mathematical modelling of cellular fate decision
Computational Biomedicine (PI: Menden) Machine learning / biostatistics methods for pharmacogenomics (drug high-throughput screens)/ Systems biology analysis of cancer and diabetes
Translational Immunoinformatics (PI: Schubert) Machine learning and Combinatorial Optimization in Computational Immunology/ Biostatistics analysis and methods development for Biomedical applications

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