Research Assistant / Associate (f/m/d) - DTXplore - ontology ms

Weitere Informationen

The successful candidate will be employed under a regular employment contract.

The position is to be filled by 9/1/2026 and offered for a fixed term of 3 years.

The fixed-term employment is possible as it constitutes one of the fixed-term options of the Wissenschaftszeitvertragsgesetz (German Act on Fixed-term Scientific Contracts).

This is a part-time position (75 % of the standard weekly hours for full-time employees).

The successful candidate has the opportunity to pursue a doctoral degree in this position.

The salary is based on the German public service salary scale (TV-L).

The position corresponds to a pay grade of EG 13 TV-L.

Unser Profil

The research focus at the Chair CG³ of RWTH Aachen University lies in applied geophysics and numerical simulation in the geosciences. We develop innovative approaches for the characterisation and prediction of subsurface processes, combining geological modelling, data integration, artificial intelligence, and uncertainty quantification .

We are actively involved in the development of scientific open-source software (e.g. GemPy) and work at the interface of geoscience, computational science, and machine learning.

In teaching, we contribute to the B.Sc./M.Sc. programmes „Applied Geosciences“ and „Georesources Management“ of RWTH Aachen as well as to the international Joint M.Sc. programme „Applied Geophysics“, which we offer together with TU Delft and ETH Zurich.

Ihr Profil

You hold an above-average university degree (Master or equivalent) in Geosciences, Data Science, Computer Science, or a related field.

You have a strong interest in AI, digital geology, and knowledge representation , and ideally bring:

• programming experience (e.g. Python)
• interest in semantic technologies and/or machine learning
• ability to work independently and in an interdisciplinary team
• strong communication skills in English

Knowledge of German is an advantage.

Ihre Aufgaben

The position is embedded in the BMFTR-funded project DTXplore , which develops a digital twin framework for mineral exploration , integrating geological knowledge, geophysical data, and AI-supported modelling across multiple spatial scales.

This PhD project focuses on the development of ontology-driven AI approaches for mineral systems modelling .

Your tasks include:

• Development of a domain ontology for mineral systems , covering lithology, structure, alteration, geochemistry, and mineralization
• Integration of structured geological knowledge into AI-assisted 3D geological modelling workflows
• Development of retrieval-augmented generation (RAG) approaches to support digital twin modelling
• Application of natural language processing (NLP) to extract information from geological reports, maps, and scientific literature
• Integration of extracted knowledge into uncertainty-aware geological models
• Validation of methods using case studies in Germany and Australia
• Collaborative research-stays in Australia
• Publication of results in peer-reviewed journals and presentation at international conferences

The position offers the opportunity to establish an independent research profile at the interface of geosciences, AI, and knowledge representation , with the goal of completing a doctoral degree. In addition, participation in teaching within our B.Sc. and M.Sc. programmes (lectures, exercises, supervision of theses) is welcome.

Besoldung / Entgelt

EG 13 TV-L

EEO Statement

RWTH is an equal opportunities employer. We welcome and encourage applications from all qualified candidates and make employment decisions without regard to national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is especially committed to supporting the advancement of women in academia. When women are underrepresented in a university unit, preferential consideration will be given to female applicants among candidates of equal merit and professional standing, unless compelling reasons favor another individual.