Based on the cutting-edge research performed at CPR, the center carries out undergraduate teaching for bachelor and master students and postgraduate education and supervision at the University. Get an overview of where you as a student can meet us:
Gain insights into complex diseases such as diabetes and cancer by learning to master a range of methods for finding, analyzing and integrating heterogeneous biological data.
– International Summer School
Get a comprehensive, theoretical and practical training in state-of-the-art techniques in cellular and molecular biology characterizing protein mechanisms of action in living cells.
Learn a range of methods for finding, analyzing and integrating heterogeneous biological data in the context of a specific disease, and to critically evaluate results of such analyses.
Learn to analyze and process large biological data sets by writing and running Python programs.
Get an introduction to cutting-edge cellular, molecular, and computational approaches to investigation of disease-related proteins, stem cell biology; regulation of metabolism, and cell factory engineering.
Get training in how to analyze data and think critically about state-of-the-art techniques in cellular, molecular, and computational biology characterizing protein mechanisms of action in living cells.
Gain insights into the major high-end proteomics technologies and workflows and learn to design experiments and analyze data.
Learn central aspects of omics studies in order to design studies and critically evaluate results from studies of genomics, transcriptomics, proteomics, metabolomics and bioinformatics in humans.
Get an overview of the major high-end quantitative proteomics technologies and their applications in biology.
Learn advanced research methodologies to characterize protein mechanisms focusing on gene editing and cryo-EM.
Learn how to get data access to big data of various types and of a range of methods, including machine learning and biological network analysis, for finding, analyzing and integrating heterogeneous data in the context of a specific disease.