PhD Position - Representation and Active Learning for Multi-Scale Scientific Imaging

id="offer-description" class="ecl-u-type-heading-2 ecl-u-mt-none ecl-u-mb-l">Offer Description Area of research: . PHD Thesis. Job description: PhD Position - Representation and Active Learning for Multi-Scale Scientific Imaging . 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. Your Job . The PhD project is methodologically independent and embedded in a multidisciplinary research environment at the interface of artificial intelligence, scientific