PhD researcher in information retrieval and retrieval-augmented generation (f/m/d, E13 TV-L, 75%)
The University of Tuebingen, through its Institute for Applied Medical Informatics, is offering a funded PhD researcher position in information retrieval and retrieval-augmented generation. The position is supervised by Junior Professor Harry Scells, who leads the Human Language Technologies group. The research focus is on developing advanced neural retrieval and ranking models to facilitate the effective retrieval of scientific literature from large-scale repositories such as PubMed. The role also involves advancing retrieval-augmented generation (RAG) techniques to support both qualitative and quantitative synthesis of scientific evidence, and investigating robust evaluation methods for domain-specific IR and RAG approaches.
The successful candidate will join a dynamic, international team and collaborate with colleagues and peers on projects related to information retrieval, natural language processing, and their applications in health and medicine. Responsibilities include publishing high-quality papers and presenting research at leading IR and NLP conferences. The University of Tuebingen is committed to diversity, inclusion, and equal opportunity, and encourages applications from underrepresented groups in science. Severely handicapped persons with equal qualifications are given preferential consideration.
Applicants must hold a completed M.Sc. degree in computer science, machine learning, or related fields, and demonstrate strong proficiency in English. Preferred qualifications include technical understanding of transformer language models, knowledge of IR fundamentals, and experience with machine learning libraries such as PyTorch. The position is funded according to the German public sector pay scale (E13 TV-L, 75%), offering a competitive salary and benefits.
To apply, candidates should send a single PDF containing a cover letter (describing research interests and motivation), CV, transcripts, diplomas, and an overview of skills and techniques to [email protected]. The application deadline is April 30, 2026. For further information about the institute and research group, visit the academic page provided.
This opportunity is ideal for candidates interested in cutting-edge research at the intersection of information retrieval, machine learning, and medical informatics, with a strong emphasis on collaborative and impactful work in health-related domains.
