Computer Scientist / PhD Researcher in Machine Learning | Informatiker (m/w/d)
Forschungszentrum Jülich GmbH
Job Summary
This role at the Institute for Materials Data Science and Informatics (IAS-9) at Forschungszentrum Jülich focuses on developing foundational Machine Learning and AI methods for scientific imaging and materials discovery. As a PhD candidate, you will work within a multidisciplinary team to bridge data-driven approaches with domain knowledge. Your daily responsibilities include developing multi-scale representation learning methods, designing active learning strategies for experimental design, and building surrogate models to connect imaging data with physical properties. This position is particularly attractive due to its integration with the Jülich Supercomputing Center and the Ernst Ruska-Centre, offering access to high-performance computing and unique scientific infrastructures. You will have the opportunity to publish in high-impact journals and contribute to open-source software while working on high-stakes projects like sustainable steel development. This is an ideal role for a researcher looking to solve fundamental AI questions within a real-world scientific context.
Required Skills
Education
Master's degree or equivalent in Computer Science, Data Science, Applied Mathematics, Physics, Materials Science, or a related field.
Experience
- Professional experience in machine learning and/or computer vision
- Experience with Python and modern ML frameworks such as PyTorch or TensorFlow
- Experience in interdisciplinary research environments is preferred
- Experience in publishing scientific results in journals or conferences
- Experience with scientific or microscopy data is welcome but not required
Languages
Additional
- The candidate must be able to work in a multidisciplinary team and have strong analytical skills. The role involves contributing to open-source research software and collaborating with experimental partners.
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