About this role
In order to fill a fixed-term position in full-time (39.83 hours/week = 100%) at the earliest possible date, we are looking for a Doctoral Researcher (m/f/x) The Interdisciplinary Centre for Advanced Materials Simulation (ICAMS) is a research centre at the Ruhr University Bochum, focusing on the development and application of multi-scale simulation tools for advanced materials. ICAMS is embedded into a network of national and international collaborations. Researchers and students benefit from this top international and interdisciplinary environment. The research group Materials Informatics and Data Science is looking for a researcher at the intersection of Materials and Natural Language Processing. The tasks associated with the offered position include the development and benchmarking of methods for reproducible knowledge extraction from the scientific literature, organizing this knowledge using field-specific ontologies and their extensions, development and publication of benchmarks with provenance information beyond composition-property relationships. Scope: full-time Duration: fixed-term, 2 years Start: at the earliest possible date Apply by: 2026-08-31 Your tasks: - Large-scale Large Language Model deployment on materials science literature, possibly also fine-tuning - Task-specific prompt optimization - Usage and extension of materials science domain ontologies for simulations and experiments - Creation of reference benchmarks for extraction tasks - Reproduction of published computational results based on extracted workflow parameters Your profile: - Outstanding, science-driven candidate with strong programming capabilities and a Master of Science in Materials Science, Physics, Chemistry, or related fields - Proven prior (scientific) expertise with Natural Language Processing, in particular Large Language Models, is a must - Expertise and experience with workflow managers and associated software packages (e.g, pyiron, Aiida, ase, etc.) for atomistic materials simulations (e.g. VASP, LAMMPS) is a must - Experience using UNIX-like operating systems - Demonstrated experience in scientific software development (e.g. Python), reproducible workflows, testing, continuous integration and software version control with git - Prior teaching experience in “Machine Learning for Materials/Materials Informatics/Artificial Intelligence in Materials Science and Engineering” is a bonus - Experience with domain-specific ontologies is beneficial - Experience in deploying local open-weight models is beneficial https://jobs.ruhr-uni-bochum.de/jobposting/a6d0d6cfd0d1272ca7c2f0df55e67cc7cf907e710?ref=AfA ( https://jobs.ruhr-uni-bochum.de/jobposting/a6d0d6cfd0d1272ca7c2f0df55e67cc7cf907e710?ref=AfA )