Tenure Track Assistant Professor in Mathematics of Machine Learning Technical University of Mun
in
80331, München, Bayern, Deutschland
Verfasst am 2026-10-09
Unternehmen:
Euro Math Soc
Vollzeit
position Verfasst am 2026-10-09
Berufliche Spezialisierung:
-
Erzieher
Universitätsprofessor, Datenwissenschaftler, Mathematik, Akademisch
Stellenbeschreibung
The Technical University of Munich (TUM) invites applications for the position of Tenure Track Assistant Professorin » Mathematics of Machine Learning «to begin as soon as possible. The position is a W2 fixed-term (6 year) tenure-track professorship with the possibility for promotion to a tenured W3 position.
Scientific Environment The professorship will be assigned to the Department of Mathematics in the TUM School of Computation, Information and Technology.
Responsibilities The responsibilities include research and teaching as well as the promotion of early-career scientists. The professorship “Mathematics of Machine Learning” offers an exciting opportunity to shape the future of mathematical research in machine learning at the Technical University of Munich (TUM). The successful candidate will play a key role in integrating cutting-edge developments – such as deep learning, generative models, and robust learning methods – into the research and teaching activities of the TUM CIT Department of Mathematics, further strengthening the central role of mathematics in the foundations of artificial intelligence.
We seek to appoint an internationally competitive researcher with an outstanding academic track record and deep expertise in one of the following fields:
• Mathematical Analysis (e.g., functional analysis, harmonic analysis, approximation theory)
• Optimization• Probability Theory and Mathematical Statistics.
We particularly value research that bridges these areas in a non-trivial and innovative way – ideally leading to significant advances in the understanding of the expressiveness, training dynamics, stability, and generalization behavior of machine learning models. A strong ability to develop new machine learning methodologies and to rigorously analyze them using mathematical tools is essential.
The successful candidate is also expected to be closely involved in TUM’s strategic AI initiatives and research infrastructure. Relevant institutional partners include the Munich Data Science Institute (MDSI), the Munich Institute of Robotics and Machine Intelligence (MIRMI), the Munich Center for Machine Learning (MCML), the Munich ELLIS Unit, and the Konrad Zuse School of Excellence in Reliable AI. These collaborations offer unique opportunities for interdisciplinary research and impact.
The professorship includes teaching responsibilities in the international Master’s program Mathematics in Data Science, as well as in related core areas of mathematics such as analysis, optimization, probability theory, and statistics. A suitable contribution to the teaching of mathematics in the Bachelor’s programs and for other TUM Schools is expected.
Qualifications We are looking for candidates who have demonstrated initial scientific achievements and the capacity for independent research at the highest international level. A university degree and an outstanding doctoral degree or equivalent scientific qualification, as well as pedagogical aptitude, are prerequisites. Substantial research experience abroad is expected (please see for further information).Our Offer Based on the best international standards and transparent performance criteria, TUM offers a merit-based academic career path for tenure track faculty from Assistant Professor through a permanent position as Associate Professor, and on to Full Professor.
The regulations of the TUM Faculty Recruitment and Career System apply.
TUM provides excellent working conditions in a lively scientific community, embedded in the vibrant research environment of the Greater Munich Area. The TUM environment is multicultural, with English serving as a common interface for scientific interaction. TUM offers attractive and performance-based salary conditions and…
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