Independent Research Group Leaders (f/m/d)

Modeling Biological and Biochemical Systems: Development of mathematical, multi-scale, and agent-based models to link molecular and cellular behavior. Integration of experimental data (omics, imaging, spectroscopy) into predictive computational frameworks. Application of advanced computational techniques - finite element modeling, triangulated meshes, modeling of protein-protein or protein-RNA interactions, and statistical inference to explore emergent properties in living systems. AI and Machine Learning for Data-Driven Discovery: Design and training of deep learning and generative models to analyze large-scale imaging and omics datasets. Application of AI to automate pattern recognition, structure reconstruction, and hypothesis generation. Application of cutting-edge machine learning to uncover new insights into molecular and subcellular organization. Large Language Models and Human-Machine Interaction: Development of LLM-based tools that translate natural language queries into computational workflows. Creation of interfaces enabling non-programmers to simulate, analyze, and interpret biological data seamlessly. Integration of LLMs with existing scientific computing and molecular simulation frameworks. I ntegrative Structural Cell Biology: Integration of Structural Biology and Software Engineering. Integration of multimodal datasets (X-ray, Cryo-EM, VolumeEM, super-resolution, single-molecule spectroscopy, spatial omics) for comprehensive molecular modeling. Development of visualization, analysis, and data management software to support large collaborative studies. Digital twins: Conceptual research on the generation of digital twins. Application and evaluation of digital twins in life sciences. Research on interfaces between cells and informatics. Computational prediction and control of cellular behavior.