PhD Researchers — LLM Pre-Training

At the University of Göttingen -Public Law Foundation-, Institut für Informatik, there are 2 positions as

PhD Researchers — LLM Pre-Training & RAG (all genders welcome)

Entgeltgruppe 13 TV-L/100%

to be filled. Starting date is 12/1/2025. The position is fixed-term until 11/30/2028.

The Chair of Scientific Information Analytics, headed by Prof. Dr. Bela Gipp (GippLab — ), conducts research at the intersection of computer science, data science, and information science. Natural language processing (NLP) based on Large Language Models (LLM) is a particular research focus of the chair.

As part of the research project LibraryAI — LLM Pre-Training and RAG for Libraries ( more information ), we are looking for two full-time positions for PhD researchers (all genders welcome).

Short Project Description: Libraries have long evolved—from scrolls to books to computerized catalogs and web-scale discovery services. With generative AI, the next transformation is already taking shape. The LibraryAI project proposes to design, develop, and test a virtual research assistant powered by Large Language Models and Retrieval-Augmented Generation (RAG) to support library users.

This project is a joint effort between the University of Göttingen (UGoe), the Göttingen State and University Library (SUB), and the GWDG (Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen). Our multidisciplinary team brings together expertise in library science, computer science, and data management. Moreover, the project can leverage significant data and high-performance computing resources. This blend of domain-specific knowledge, technical skill, and data infrastructure will empower us to devise, implement, and deploy a capable, robust, and efficient language model along with a user-friendly interface.

LibraryAI will be agnostic to the underlying library systems and collections, feature a modular architecture, and be made openly accessible to ensure its adaptability for other libraries.

Areas of Responsibility

• Adapt and fine-tune existing open-source language models using transfer learning to meet the specific needs of the library and its diverse scientific collections.
• Integrate the LLM with an information retrieval system that accesses the library's most current content, ensuring answers are up-to-date and factually grounded.
• Design, implement, and test an integrated solution that combines LLMs, RAG, and agents to use external tools and APIs, enabling it to query the library catalogue, check for book availability, access digital repositories, and answer questions about library services.
• Develop and train models based on PPO, GRPO, and RLVR to align models to human preferences.
• Contribute to front- and back-end development for the project.
• Collaborate with an interdisciplinary team of subject matter experts, data specialists, and project partners, including the GWDG.
• Contribute to the development of a robust and sustainable MLOps pipeline for real-world use in libraries.
• Engage in the development of project frameworks and support partners in deploying models within user-facing web applications.
• Publish your research findings at leading NLP conferences (e.g., ACL, EMNLP, NAACL).
• Conduct teaching in accordance with the requirements of the PhD program in computer science at the University of Göttingen (low workload).
• Supervise bachelor's and master's students working on related projects.

Your Profile

• A master's degree with a grade of "very good" (or equivalent) in computer science, computational linguistics, data science, or a related discipline.
• Strong programming skills, particularly in Python.
• Hands-on experience with deep learning frameworks (e.g., PyTorch) and NLP libraries (e.g., Hugging Face).
• Solid foundation in NLP downstream tasks (e.g., NER, tokenization, word sense disambiguation).
• Professional fluency (C1) in German and English, both written and spoken.
• Communicative and teamwork-oriented mindset.

We Offer

• A stimulating, interdisciplinary, and international research environment at one of Germany's top-tier universities.
• The chance to contribute to a high-impact project at the intersection of AI, linguistics, and cultural heritage.
• Close, supportive supervision to foster both your academic and personal development toward a PhD.
• Access to cutting-edge HPC resources, such as a GPU cluster with NVIDIA A100 GPUs, is essential for large-scale model training.
• Funding to present your research at premier international conferences and engage with the global scientific community.
• A full-time position with a competitive salary under the German public service scale (TV-L), with the option of part-time employment.
• Office space and technical equipment. The position will be located in Göttingen on-site.

This role requires regular on-site presence in Göttingen; remote work is possible to a limited extent.

The University of Göttingen is an equal opportunities employer and places particular emphasis on fostering career opportunities for women. Qualified women are therefore strongly encouraged to apply in fields in which they are underrepresented. The university has committed itself to being a family-friendly institution and supports their employees in balancing work and family life. The University is particularly committed to the professional participation of severely disabled employees and therefore welcomes applications from severely disabled people. In the case of equal qualifications, applications from people with severe disabilities will be given preference. A disability or equality is to be included in the application in order to protect the interests of the applicant.

Please upload your application in one pdf file including the usual documents until 10/29/2025 on the application portal of the university using this link: . For more information get in touch with PD Dr. Terry Lima Ruas directly via E-Mail: -, Tel

Please note:

With submission of your application, you accept the processing of your applicant data in terms of data-protection law. Further information on the legal basis and data usage is provided in the Information General Data Protection Regulation (GDPR)