PhD Student/Doctoral Candidate in Machine Learning at the Computational Law Lab University of Tübingen in Germany

The Computational Law Lab at the University of Tübingen is offering a fully funded PhD position in Machine Learning, with a focus on interdisciplinary research at the interface of technology and law. This three-year doctoral opportunity is part of the Horizon Europe project ELLIOT, which aims to develop open, multimodal foundation models capable of robust generalization across real-world, noisy, and dynamic data streams. The lab is renowned for its innovative approach to combining machine learning with legal research, and this project will specifically investigate large-scale data annotation strategies, algorithm development for automatic detection of legal categories, and benchmarking foundational models on diverse datasets.

Supervised by Prof. Dr. Hilde Kühne and Dr. Kristof Meding, the successful candidate will join a vibrant research environment dedicated to advancing privacy protection and enhancing the deployment of next-generation multimodal models. The position offers remuneration according to the E 13 TV-L collective agreement (75% FTE), providing a competitive salary and benefits for three years.

Applicants should hold a Master’s degree in a STEM field such as computer science or a related discipline. Essential qualifications include a strong academic background in machine learning, computer vision, or natural language processing, excellent programming skills in Python, and solid mathematical foundations in linear algebra, probability, and statistics. While no prior legal knowledge is required, candidates should be open to engaging with interdisciplinary topics at the intersection of technology and law.

The University of Tübingen encourages applications from women and individuals with disabilities, aiming to foster diversity in research and teaching. Formal employment procedures will be managed by the university’s central administration.

To apply, candidates should submit a single PDF file containing a cover letter (indicating primary research interests), a detailed curriculum vitae, degree certificates, and contact details of two referees. Applications and inquiries should be directed to Dr. Kristof Meding at [email protected]. The application deadline is January 21, 2026. For further details, refer to the official job advertisement: PhD Student/Doctoral Candidate in Machine Learning.