We strive to understand how genomes coordinate transcription within the context of nuclear organization to guide complex developmental decisions. We create novel tools and approaches for single-cell biology.

Combining engineering and biological approaches, Matthias lab aims to understand the role of natural stem cell niches mechanistically and simulate /manipulate them reproducibly unde rlaboratory conditions. 

Celia´s lab aims to differentiated "molecular age" and "chronological age". Novel molecular featureswill be useful to decipher the impact of cellular variability on tissue function, during ageing and in chronic diseases.

The vision of Boyan´s Team is to understand the genomic blueprints guiding billions of neurons to assemble into the most complex organ in the universe - the humain brain. 

Marion´s Team uses in situ cryo-electron tomography methodologies, including correlative cryo-focused ion beam milling sample preparation and image processing to reveal actin architectures directly inside the native cellular environment.

We are a diverse team of researchers asking interdisciplinary questions, and engaging in multidisciplinary approaches, in the hopes of achieving transdisciplinary outcomes (transcending disciplines).

Our group’s primary research focus is the role of mechanics in human disease, especially of the lung. We leverage quantitative imaging and bioengineering to study mechanisms at different temporal and spatial scales.

Our research is dedicated to the development of excellent techniques for biomedical imaging. The advancement of new targeted contrast agents and novel imaging modalities will pave the way for personalized therapy.

Our aims are to use large-scale population-based association approaches to identify heterogenous subtypes of MDD. We follow up genetic association results with multi-omics investigations to reveal molecular mechanisms.

We advance human disease research by combining human genetics with AI-driven analyses of high-content phenotypes.

We study how genomics in combination with Artificial Intelligence can benefit One Health, which affirms that human health and the health of our planet are inextricably linked.

Our research agenda is to create, cultivate, and critique multi-scale analyses tools based on topological machine learning techniques, with a specific focus on healthcare topics.