About us:

The Group for Mathematical Data Science at LMU Munich conducts fundamental mathematical research in the fields of data and signal processing, and machine learning. A particular focus is on the development of reliable compression methods and the efficient use of data. The group is affiliated with the Munich Center for Machine Learning (MCML) and the Chair of Mathematical Foundations of Artificial Intelligence at LMU, which plays a leading role in various major initiatives, such as the AI-HUB@LMU and the Konrad Zuse School of Excellence in Reliable AI.

We are looking for you:

Doctoral student (m/f/x)

in Munich

Your tasks and responsibilities:

The position is part of an NWO-DFG-funded project on high-dimensional covariance estimation and will be carried out in close collaboration with Sjoerd Dirksen, Johannes Maly, and a postdoc who will be hired at Utrecht University. During the project, you will visit Utrecht University several times (once for two months, twice for one week) to work on-site with the project partners. The work on the project includes the following tasks:

• Research on one-bit quantization in the context of covariance estimation, extending and deepening the following works (preprints are available on arxiv.org)
• Publication of results in national and international journals
• Participation in teaching is possible, but not mandatory

Your qualifications:

• You have a master’s degree in mathematics with very good grades, preferably with a focus on calculus or probability theory
• You have basic programming skills
• You are fully proficient in spoken and written English

Benefits:

• a cutting-edge field of research
• the opportunity to pursue a Ph.D.
• a pleasant, collegial work environment in a highly international department
• a workplace in a central location in Munich that is easily accessible by public transportation

Salary will be determined based on qualifications and professional experience, up to TV-L E13. The LMU Munich is committed to increasing the proportion of women among its academic staff and strongly encourages qualified women to apply.

People with disabilities who are equally as qualified as other applicants will receive preferential treatment.

Contact:

We are looking forward to receiving your application via email (as a single PDF file, maximum 5 MB) with the standard documents (cover letter, cv, copies of diplomas and certificates, and contact information for two references) by 18.06.2026 via e-mail through the “online application” function.

Contact for inquiries: Prof. Dr. Johannes Maly

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