Marvin Poul

Marvin Poul is a Researcher at the Max Planck Institute for Sustainable Materials in Düsseldorf, Germany. His primary affiliation is with the Department of Computational Materials Design, focusing on interdisciplinary research at the intersection of materials science, computational physics, and machine learning. His work emphasizes the computational modeling of material defects, thermodynamic property prediction, and automated machine learning potential development.

Research Interests:
- Thermodynamics of Defects
- Atomistic Simulations of Material Microstructures
- Machine Learning-Driven Materials Design
- Computational Approaches to Defect Phase Diagrams
- High-Throughput Materials Informatics

Recent publications highlight advancements in:
- Automated generation of structure datasets for machine learning
- Sampling-free computation of thermal material properties
- Dislocation dynamics in electrical steel grain growth

He contributes to open-source tools such as the pyiron framework for computational workflows. No scientific awards are explicitly listed, but his active research profile indicates significant contributions to computational materials science.