About the opportunity
The Chair for ‘Trustworthy Human Language Technologies’ at the Faculty of Computer Science focuses on natural language processing in the legal field and under data protection compliance. The TransparentNLP BMFTR joint project aims to develop a novel privacy-enhancing technology enabling large language models to truthfully and understandably answer questions regarding personal data processing, fulfilling EU legislation transparency principles. This subproject focuses on realizing a robust and verifiable Retrieval-Augmented Generation (RAG) framework for automated compliance question-answering. Responsibilities center on technical system development, modular pipeline implementation, and iterative evaluation.
Salary and benefits
- Comprehensive training and professional development opportunities
- Collaboration within a dedicated and appreciative team
- Challenging and varied tasks with high personal responsibility
- Employment under the Collective Agreement for the Public Service of the Federal States (TV-L, Entgeltgruppe E13)
- No obligation to undertake teaching duties if funded exclusively by external third-party grants
Who can apply?
- Master's degree in Computer Science (completed or nearly completed; degree must be obtained by the time of appointment) or related fields
- Experience in Machine Learning, NLP, and Data Science
- Knowledge of Python, C, C++, Java, and Lua
- German language proficiency of at least C1 level for the project consortium
- Application of Data Science, AI, and NLP methods for large dataset analysis
- Completed courses in Deep Learning, supervised methods, unsupervised methods, evolutionary algorithms, machine learning theory, and natural language processing with deep learning
Required documents
- Cover letter
- Tabular curriculum vitae
- Certificates (e.g., employment certificates, degree certificates, training certificates)
When to apply
- Applications are accepted until September 21, 2026, referencing application number ANR 6080.
How to apply
- Submit your application with reference number ANR 6080 via the official online application portal.
- Alternatively, apply via email to the address provided in the official posting including all required application documents.
Additional information
- The workplace is Ruhr-Universität Bochum.
- Campus languages are German and English. Proficiency in at least one and the willingness to learn the other is required.
- The Staff Council has the right to participate in all selection interviews.
- Travel and interview costs cannot be reimbursed.
Our Take on This Opportunity
This section reflects Open Opportunities’ own analysis of the opportunity from an applicant’s perspective.
You may be a strong fit if…
- Completed or nearly completed Master's degree in Computer Science or a closely related field
- Practical experience in Machine Learning, Natural Language Processing, and Data Science
- Familiarity with programming languages such as Python, C, C++, Java, and Lua
- Completed coursework in Deep Learning, supervised and unsupervised methods, and natural language processing
What should you think carefully about?
- Candidates must possess a German language proficiency of at least C1 level for the project consortium
- The role is an on-site position located at Ruhr-Universität Bochum in Germany
- Applicants must verify travel and interview cost policies, as expenses cannot be reimbursed
How could this fit your current goals and plans?
This position offers a valuable chance to contribute to privacy-enhancing technologies and RAG frameworks within a collaborative academic joint project.
Our take
Computer science graduates with strong NLP skills and advanced German proficiency should strongly consider this role, whereas applicants without the required C1 German level will not qualify.
Ready to apply?
Review the opportunity on the official website before applying.
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