PhD and postdoc positions, RWTH Aachen University

At Chair C for Mathematics of RWTH Aachen University, we are presently looking for candidates for several doctoral and postdoc positions in the mathematical foundations of compressive sensing, of covariance estimation and of machine learning with neural networks.

Candidates are expected to have a strong mathematical background in one or more of the following areas: (high-dimensional) probability theory, compressive sensing, mathematical signal processing, continuous optimization, neural networks, covariance estimation, dynamical systems, approximation theory.

Candidates are expected to contribute to the teaching duties of the chair. Knowledge of the German language will not be necessary in the beginning, but candidates are expected to develop sufficient German skills for teaching during the first 2 years.

Starting date: flexible, but preferably as soon as possible.
Salary: 75% of TV-L 13 (doctoral students) or 100% of TV-L 13 (postdocs). A rough estimate of the salary can be found via the website
Duration: Initial contract for 2 years, with possible extension.
Requirements: Completed master degree in mathematics or equivalent degree (doctoral students) or completed doctoral degree in mathematics or equivalent degree (postdocs).

Please send your application in pdf-format to and until August 6, 2018. Your application should include the following documentation:

Curriculum Vitae, including list of publications (if any), electronic copy of master and/or doctoral thesis, certificates of academic degrees, at least one letter of recommendation and/or name and email address of a potential reference person.

Late applications will be considered until the positions are filled. Recommendation letters should be sent directly via e-mail by the reference persons. The required academic degree may still be in the process of completion at the time of application, but the candidate must hold the degree at the start of the position.

For further inquiries, please send an e-mail to or

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