OUR RESEARCH AREAS

Discover our interdisciplinary research fields

The Max Planck School of Biomedical AI unites expertise from artificial intelligence, biology, biomedicine, computer science, physics, chemistry, and mathematics. Across four interconnected research areas, doctoral researchers develop AI methods that address fundamental challenges at the interface of artificial intelligence and the life sciences.

1. AI for Understanding Molecular and Cellular Systems

This research area develops AI methods to analyze and integrate multimodal biological data, from proteomics and spatial omics to live-cell imaging. Combining machine learning with experimental biology, researchers uncover the molecular and cellular principles that govern biology at its core.

2. AI for Protein and Molecule Design

Researchers develop generative AI models to design proteins and other biomolecules while incorporating physical and chemical constraints. Machine learning, molecular modeling, and experimental validation are closely integrated in an iterative research process.

3. Modelling Complex Biological Traits from Multi-Scale Data

This research area develops AI methods to model and predict complex biological traits by integrating data across multiple biological scales. Researchers link genetic variation, cellular states, imaging data, and behavior to better understand how biological systems function.

4. AI for Neural Network Exploration

Researchers develop explainable AI methods to study biological neural networks from molecules to whole-brain circuits. Combining neuroscience, brain network analysis, and machine learning, they investigate the organization and dynamics of neural networks in health and disease.

All of our Fellows contribute expertise across one or more of these research areas. Learn more about their research and backgrounds.