PhD Student (m/w/d)

Conducting research for a changing society

this is what drives us at Forschungszentrum Jülich. As a member of the Helmholtz Association, we aim to tackle the grand societal challenges of our time and conduct interdisciplinary research into a digitalized society, a climate-friendly energy system, and a sustainable economy. Work together with some 7,600 employees in one of Europe’s biggest research centres and help us to shape change!

The Institute for Materials Data Science and Informatics (IAS-9) develops advanced Machine Learning & Artificial Intelligence methods tailored to challenges in the physical sciences and engineering, bridging data-driven approaches with domain knowledge to push the boundaries of scientific discovery. Our group brings together ML engineers, AI researchers, data scientists, research software engineers, and domain scientists with a shared focus on scientific machine learning. Together, we develop and apply ML methods to tackle key challenges in the physical sciences and engineering: from accelerating simulations with surrogate models to extracting insights from complex imaging data, and building approaches that transfer across domains.
In addition, we benefit from a strong connection to the Ernst-Ruska-Centre for Electron Microscopy and to the Jülich Supercomputing Center. We are particularly interested in advancing foundational machine learning methods for scientific imaging, with a focus on representation learning and data-efficient decision-making across heterogeneous data sources.