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The Graduate School of Quantitative Biosciences Munich


The Graduate School of Quantitative Biosciences Munich (QBM) offers PhD Positions for students with a background in biochemistry, biology, bioinformatics, physics or applied mathematics, and an interest in conducting interdisciplinary research at the interface of experiment and quantitative theory.

The Graduate School seeks to prepare young life scientists for the emerging era of quantitative, systems-oriented bioscience. It provides an innovative, international PhD training program that bridges the divide between traditionally separate disciplines, from biochemistry and medicine to bioinformatics, experimental and theoretical biophysics, and applied mathematics. While maintaining a strong command of their ‘home’ discipline, QBM students will become knowledgeable in multiple approaches and styles of thought and learn to communicate and work effectively with scientists from different backgrounds.

Key elements of the QBM program are:
     •   an interdisciplinary research project
     •   a substantial program of formal coursework with a general and an individual component, centred
          around an interdisciplinary core course that covers key problems in bioscience from multiple
     •   a multi-faceted mentoring and professional skills program designed to promote students’ growth as
          independent scientists

QBM is a joint initiative by leading scientists from the Ludwig-Maximilians-University Munich, the Max-Planck Institute of Biochemistry, the Helmholtz Center Munich, and the Technical University Munich. Research within QBM encompasses the entire range of approaches brought to biological questions today, with two major trajectories with complementary perspectives: reductionist and holistic.

The reductionists are represented by biochemists and biophysicists who work with well-circumscribed, often simple systems that perform a particular task, such as DNA repair, chromatin remodelling, translation and folding of proteins, or the degradation of RNA or proteins. They use structural biology (x-ray crystallography, cryo-electron microscopy) and single molecule techniques (super-resolution microscopy, atomic force measurements, magnetic tweezers) to understand how these molecular machines work at the highest possible resolution, down to the stochastic behaviour of individual protein complexes. Similarly, synthetic biologists and theoretical biophysicists seek to create, understand and predict the minimal systems that are capable of producing emergent properties, such as pattern formation under normal and perturbed conditions. Eventually, of course, the reductionists want to know how their well-defined molecular machines deal with the complex mixture of substrates/targets present in the cell.

The holists are represented by biologists, medical researchers, and computational biologists. They work with complex biological systems as present in nature and seek to characterize specific processes, in particular, regulatory networks and signalling pathways such as those involved in cell proliferation, death and differentiation or innate immunity. The objectives are to identify the participating components by genetic methods (forward/reverse genetics, RNAi, CRISPR), to track their physical interactions using genetic or biochemical, as well as a wide range of -omics approaches, such as next generation sequencing (DNase-Seq, ChIP-Seq, RNA-Seq) or proteomics (Y2H, mass spectrometry). By applying machine learning and pattern recognition methods aided by the power of high throughput experimentation, these researchers seek to generate quantitative mechanistic models which capture the behaviour of complex live systems as realistically as possible.

The ultimate goal of the research conducted within QBM is therefore to develop quantitative models that describe the behaviour of complex biological systems with high fidelity and molecular resolution.

Student interview

What did you expect to learn at QBM?

As a molecular biologist by training, I saw QBM as a great chance to gain more experience in genome-wide sequencing assays and learn more about the associated data processing and analysis.

Did it work out?

QBM made my transition to the field of systems biology very smooth, not only by offering lectures and tutorials on statistics and programming but also creating an interdisciplinary environment. For more than a year now, I have been closely collaborating with another QBM student, who is developing data analysis workflows for my DNase-seq and ATAC-seq data.

What are the challenges?

Initially, it was challenging for us, a molecular biologist and a computer scientist, to develop a common language. By now, I find this collaboration very enjoyable and rewarding, and it is also a great opportunity to learn something new from each other.

What are the benefits of QBM?

The newest technologies are easily accessible through the program. It opens the gates for development of practical knowledge of novel experimental techniques such as super-resolution microscopy, next generation sequencing etc. QBM provides a great international scientific environment with plenty of opportunities for discussion with the leading scientists in each field.