Research Topics
Find out more about the cutting-edge research topics investigated across our different research groups to help you navigate the list below.
Unique in the world and waiting for you!
Applicants are asked to select specific groups in their online application form as indication of interest. Please note that the list below is preliminary and may change prior to the interviews. All eligible applications will be available to all recruiting Group Leaders to review and select candidates for interviews.
Read more about the application process here.
The list below shows Group Leaders with open positions in the 2026 Winter Recruitment. The list is preliminary and may be subject to change.
Find out more about the cutting-edge research topics investigated across our different research groups to help you navigate the list below.
Self-organisation in the central nervous system
The Stuart group studies self-organization during development and regeneration of the central nervous system, comparing 3D organoids from human, mouse and axolotl, integrated with embryology, mathematical modelling and bioengineering.
(Full group page coming soon)
Somatic evolution and phylogenetics
We study how normal cells in different tissues acquire somatic mutations, use mutations as inherent barcodes to study human development and the origins of cancer, and develop computational tools to analyse mutations in novel single-cell and spatial data.
Cell Profiling for Toxicology
Our group uses machine learning and multi-omics integration to identify and characterise chemical hazards to humans and ecosystems. We analyse omics data measured after cellular perturbations, with a particular interest in image-based cell profiling.
Computational metagenomics and analysis
The Finn research group focuses on developing computational approaches for the reconstruction of genomes from metagenomes, and investigates the distribution of microbes and functions in different environments.
Pathogen informatics and modelling
Our group develops bioinformatic and mathematical modelling approaches to use sequencing data to better control pathogen threats. In particular, we study genome evolution, transmission, and the effects of vaccines and antimicrobial resistance in bacterial populations.
Systems biomedicine
Our goal is to acquire a functional understanding of the deregulation of cellular networks in disease and to apply this knowledge to develop novel therapeutics. We focus on cancer, auto-immune and fibrotic disease. Towards this goal, we integrate big (‘Omics’) data with mechanistic molecular knowledge into statistical and machine learning methods, and we share our tools as free open-source packages.
Structural biology of ubiquitin signalling
The Bhogaraju group uses structural and cell biology-based approaches to study ubiquitination pathways in normal physiology and disease.
Multi-scale imaging for evolutionary cell biology
The Wollweber group develops and applies multi-scale imaging methods – such as cryo-electron tomography and expansion microscopy – to decipher the cell biology of non-model organisms and understand the evolution of complex life.
No recruiting GTLs
Understanding cross-scale principles of cellular organisation
The Banterle group studies how the ultrastructure of macromolecular complexes can influence cell physiology, using centrioles as a model paradigm. To bridge spatial scales, we use a combination of high-speed atomic force and super-resolution microscopy, together with cellular assays.
Mechanobiology at the cell surface
The Diz-Muñoz lab studies how mechanics at the cell periphery govern function, with a focus on morphogenesis, migration, and fate in animal cells.
Theory of cellular and multicellular organisation
The Erzberger group studies the theoretical principles of self-organisation in complex systems using cellular and multicellular systems as paradigms.
Self-organisation in meiosis
The Diz-Muñoz lab studies how mechanics at the cell periphery govern The Koehler group studies how chromatin is organised during meiosis to allow for the production of haploid gametes from diploid precursor cells., with a focus on morphogenesis, migration, and fate in animal cells.
Machine learning for bioimage analysis
The Kreshuk group develops machine learning-based methods and tools for automatic segmentation, classification and analysis of biological images.
Advanced optical techniques for deep tissue microscopy
The Prevedel group develops new optical techniques for investigating dynamic cellular processes deep inside tissue in vivo.
Critical points and transitions in embryo development
The Petridou group aims to understand how complexity arises during early embryo development by focusing on the emergence and function of collective tissue properties. To do so, we combine diverse disciplines including comparative embryology, biophysics, statistical mechanics, quantitative and synthetic biology.
Symbiosis in marine unicellular eukaryotes
The Vincent group explores the diversity and impact of marine microbial interactions across different biological scales, with a focus on symbiosis within unicellular eukaryotes.
Genome regulation and chromatin topology during embryonic development
The Furlong group dissects fundamental principles of genome regulation and how that drives cell fate decisions during development, focusing on organisational and functional properties of the genome.
Quantitative Biology and Statistics
The Huber group develops statistical methods for modern biotechnologies, applies them to biological discovery, and translates them into reusable tools.
Molecular mechanisms of genomic variation and chromosome instability
The Korbel group combines computational and experimental approaches, including in single cells, to unravel determinants and consequences of germline and somatic genetic variation with a special focus on disease mechanisms.
Decoding gene regulation using single-molecule genomics
The Krebs group combines single-cell and single-molecule genomics with large-scale genome engineering to understand fundamental mechanisms for controlling gene expression.
Spatial biology from molecules to tissues: high-dimensional investigation of cellular organisation
The Saka group develops new tools and methods to investigate the spatial and molecular organisation of cells across scales. The group harnesses new labelling approaches; fluorescence, super-resolution, and correlative microscopy methods; and DNA nanotechnology.
Statistical genomics and systems genetics
The Stegle group develops and applies statistical and machine learning methods for deciphering molecular variation across individuals, space, and time.
Assembly mechanisms and function of protein-RNA complexes at the single-molecule level
The Duss group uses single-molecule methods in combination with integrative structural biological and biochemical approaches to understand how protein-RNA complexes are assembled and how macromolecular machines cooperate with each other, providing new opportunities to fight diseases and to create new functional molecular assemblies.
Exploring the chromatin landscape by cryo-electron microscopy
The Eustermann group explores the molecular landscape of chromatin to understand at an atomic level the principles underlying expression and maintenance of genomic information in eukaryotes.
In-cell structural analysis of phase separation and molecular crowding
Our group brings together two disciplines in structural and cell biology, namely the emerging field of biomolecular condensates and state-of-the-art cellular cryo-electron tomography, to advance our understanding on the functional organisation of the cytoplasm.
High-throughput cryo-EM
The Mattei team develops methods and software supporting high-throughput and fully automated pipelines to tackle the current challenges in cryo-EM sample preparation and screening.
Systems microbiology
The Typas group develops high-throughput approaches to study bacterial cellular networks in the context of their interactions with each other and their environment.
Mechanisms of embryonic gene regulation
The Boskovic group investigates epigenetic mechanisms regulating early embryonic gene expression patterns, and how their modulation influences developmental trajectories and offspring phenotypes.
Epigenetic mechanisms and intergenerational inheritance
The Hackett group investigates the role of epigenetic mechanisms in genome regulation and developmental programming, with a focus on intergenerational epigenetic inheritance. We integrate multi-omics, high-throughput (epi)genetic editing, and environmental perturbations to understand gene regulatory responses across scales, from single cells to organism phenotypes.
AI-Driven Systems for Scientific Discovery
The Petroni group builds AI solutions that combine multimodal reasoning, agentic exploration, tool usage, knowledge retrieval and lab-in-the-loop interaction to accelerate scientific discovery. We develop intelligent agents that can cross-reference large amounts of heterogeneous data sources and help scientists uncover new insights by moving beyond traditional search toward proactive discovery. Our agents are designed to identify hidden knowledge gaps, connect concepts across disciplines, and embed directly into experimental workflows to collaborate with scientists in real time.