The relAI Konrad Zuse School of Excellence in Reliable AI is now accepting applications for its 2025 PhD program, jointly organized by Ludwig-Maximilians-Universität München (LMU) and Technical University of Munich (TUM), and funded by the DAAD German Academic Exchange Service. This interdisciplinary program focuses on reliable artificial intelligence, offering research opportunities at the intersection of machine learning, mathematics, engineering, and the responsible development of AI systems. Research areas include AI safety, security, privacy, responsibility, algorithmic decision-making, robotics, healthcare, and mathematical foundations. PhD candidates benefit from a vibrant academic environment, professional development, and close collaboration with leading researchers at both LMU and TUM. Each doctoral researcher is supervised by a relAI Fellow and enrolls at either LMU or TUM, depending on the supervisor's affiliation. Notable relAI Fellows and spokespersons include Prof. Gitta Kutyniok (LMU Director of relAI School), Prof. Frauke Kreuter, Prof. Eyke Hüllermeier, Prof. David Rügamer, Prof. Albrecht Schmidt, Prof. Hinrich Schuetze, Prof. Volker Tresp, Prof. Solveig Vieluf, and Prof. Stephan Günnemann. Funded positions offer a full three-year salary (TV-L E13) and additional support such as travel grants for conferences or research stays. Applicants must hold an excellent master's degree (or equivalent) in computer science, mathematics, engineering, natural sciences, or other data science/machine learning/AI-related disciplines. A strong interest in reliable AI, including safety, security, privacy, or responsibility, is required. Proof of English proficiency at level C1 or equivalent (or proof that the degree was taught mainly in English) is mandatory. Application materials include a CV, diplomas, transcripts, a short motivation statement, choice of two preferred relAI Fellows as supervisors with explanations, names and addresses of two referees for recommendation letters, and proof of English proficiency. The application deadline is January 13, 2026. For more information and to apply, visit the official relAI application portal.

A fully funded PhD position is available in the Mathematical Foundations of Artificial Intelligence at Ludwig-Maximilians-Universität München, under the supervision of Professor Gitta Kutyniok. The successful candidate will join the vibrant Munich AI Ecosystem and the Munich Center for Machine Learning, engaging in cutting-edge research topics such as explainability, generalization, graph neural networks, inverse problems and AI, next generation AI computing, PDEs and AI, learning physical laws by AI, reliable AI, spiking neural networks, and sustainable (energy-efficient) AI. Applicants should have an excellent degree in mathematics, computer science, or a related field, and demonstrate strong analytical, programming, teamwork, and communication skills, as well as a high level of commitment and proficiency in English. The position offers a competitive salary (up to TV-L E13), flexible working hours, individual career support, and opportunities for professional development, including collaboration with leading researchers and participation in international conferences and training programs. The contract is for three years, with possible extension. Interested candidates should apply via the provided link before October 22, 2025. For more information about the research group and activities, visit the Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence website.

The Chair for Mathematical Foundations of Artificial Intelligence at Ludwig-Maximilians-Universität München, led by Professor Gitta Kutyniok, is inviting applications for a postdoctoral position in the field of AI-driven medicine, with a focus on radiotherapy. The successful candidate will join the KI-ROBUST project, which aims to develop clinically deployed AI systems for radiotherapy that automatically and precisely contour tumors, even in highly complex cases, while quantifying diagnostic uncertainty to support clinical decision-making. The overarching goal is to make treatment planning faster, safer, and more effective, with direct real-world impact. This position offers the opportunity to lead a small team, drive independent research, and actively shape the scientific direction of the project. The research environment is highly collaborative, involving world-leading partners from LMU Klinikum München, Fraunhofer ITWM, and industry partners such as Brainlab and Varian Medical Systems Imaging Laboratory Gmbh. The group is part of the Munich AI and clinical ecosystem, and is affiliated with the relAI Konrad Zuse School of Excellence, the Munich Center for Machine Learning, and the German Postdoc Network. Applicants should have an excellent PhD in mathematics, computer science, or a related field, with strong analytical and problem-solving skills, solid programming experience (e.g., Python, machine learning frameworks), a proven research track record with publications at leading venues, and the ability to drive independent research and contribute to project leadership. A structured and self-driven working style, excellent teamwork and communication skills, and a very good command of English are also required. The position is fully funded with a competitive TV-L E13 salary and offers flexible working conditions. The successful candidate will have the opportunity to shape their own research direction, contribute to high-impact publications, engage with leading academic and industry partners, and build a strong profile for the next step in their academic career. The application deadline is March 6th, 2026. For more information about the group and the position, visit the group’s academic page or the official job posting.