Join an interdisciplinary team that brings state-of-the-art AI research together with cutting-edge materials science and physics. Depending on your background you will work collaboratively on the following tasks with either with a stronger model-development or application focus:
- Design knowledge-graph-augmented transformers and retrieval-augmented generation (RAG) pipelines that enable semantic querying and reasoning over materials-science/physics corpora
- Developing pipelines for semantic enrichment of unstructured data, including entity recognition, relation extraction, and automatic ontology alignment in physics and materials domains
- Build and maintain ontologies, OWL/RDF knowledge graphs, SPARQL endpoints, and open benchmarking suites to guarantee FAIR, reusable research data
- Mine and link structure-property relationships from DFT, MD, phase-field, TEM/SEM, and other multimodal datasets from simulation and experiment
- Develop benchmarking protocols and toolkits to evaluate AI models on materials science tasks as well as integrate your semantic-AI services into high-throughput GPU/HPC workflows, contributing to data management, metadata structuring, and semantic annotation
- Collaborate with experimentalists and theorists to validate extracted knowledge via in-situ spectroscopy, synchrotron work, and high-throughput synthesis—and present your results at leading AI and materials conferences
Table of Content
Summary
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Benefits
- A dynamic, interdisciplinary research environment at the forefront of materials informatics
- Comprehensive training courses and individual opportunities for personal and professional further development. A structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors: https://www.fz-juelich.de/en/judocs
- The opportunity to attend national and international conferences
- Optimal conditions for work-life balance, including a family-friendly corporate policy, flexible working hours, the option for home office days, and 30 vacation days per year
- A creative work environment at a leading research facility, located on an attractive research campus at the TZA Aachen https://tza-aachen.de and the Forschungszentrum Jülich
- Flexible working hours in a full-time position with the option of slightly reduced working hours ( https://go.fzj.de/near-full-time )
- Targeted services for international employees, e.g. through our International Advisory Service
Requirements
- A completed university degree (Master’s or equivalent) with excellent grades in computer science, materials science, physics, or a related discipline
- Practical experience in data science, including the application of machine learning (ML) methods or large language models (LLMs)
- Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g., Git)
- Interest in or experience with semantic web technologies, including metadata schemas, ontologies, or knowledge graphs
- Excellent command of written and spoken English
- Strong communication and teamwork skills, and the ability to work effectively in an interdisciplinary and collaborative research environment
Application Deadline
Not SpecifiedHow To Apply
Are you qualified and interested in this opportunity? Kindly go to
Forschungszentrum Jülich on www.fz-juelich.de to apply
For more information, kindly visit Forschungszentrum Jülich scholarship webpage.
