The Catholic University Eichstaett-Ingolstadt (KU) invites applications for a PhD student position in the research group Reliable Machine Learning, part of the Mathematical Institute for Machine Learning and Data Science (MIDS). This position is funded by the Emmy Noether project “Stability and Solvability in Deep Learning” and the High-Tech Agenda of Bavaria. The successful candidate will join a vibrant research environment focused on the mathematical analysis of machine learning algorithms, with particular emphasis on stability, computability, and robustness in deep learning methods. The position is part-time (75%) for a duration of three years, with salary according to the TV-L Level 13 (75%) collective agreement. The research group, led by Prof. Felix Voigtlaender, offers opportunities for knowledge transfer through publications and conference participation, as well as the possibility to pursue individual research interests within the scope of the project. The KU provides a modern, team-oriented workplace with international contacts and a commitment to equal opportunities and work-life balance. Applicants should hold (or be close to completing) a master's degree in mathematics, ideally with a focus on machine learning, probability theory, real and functional analysis, or information-based complexity. Interest in the mathematical analysis of machine learning algorithms is essential, while practical experience in programming and machine learning is desirable but not mandatory. German language skills are not required, but candidates are encouraged to develop them during their employment at KU. To apply, candidates should submit a single PDF file containing a cover letter, CV, list of publications (if any), scanned certificates of academic degrees (including courses and grades), and an electronic copy or draft of their master's thesis. A letter of recommendation should also be included. Applications must be sent via email to Prof. Dr. Felix Voigtlaender at [email protected] by January 15, 2026. All application documents will be deleted after the recruitment process in compliance with data protection regulations. The KU welcomes applicants of all backgrounds and is committed to promoting equal opportunities. Candidates with severe disabilities who are equally qualified will be given priority. There are no specific denominational requirements for employment at KU, but applicants are encouraged to acknowledge the university's mission and values in their application. For further information, visit the MIDS webpage at https://www.ku.de/mids or the MathJobs listing at https://www.mathjobs.org/jobs/list/27799 .