Doctoral and postdoc positions in mathematical data science

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, machine learning, nonlinear 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 during the first 2 years.

Salary: doctoral students: 75% of TV-L 13 (German public salary scale), postdocs: 100% of TV-L 13
Duration: Initial contract for 2 years, with possible extension.
Requirements:
doctoral students: Completed Master degree in Mathematics or equivalent degree.
postdocs: Completed doctoral degree in mathematics or equivalent

Required Documents: Motivation letter, Curriculum Vitae, publications (if any), electronic copy of Master and/or doctoral thesis, certificates of academic degrees, at least one letter of recommendation and/or names of potential reference persons.

Please send your application in pdf-format to rauhut@mathc.rwth-aachen.de by February 26, 2019.
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.

If you have questions, please send an e-mail to rauhut@mathc.rwth-aachen.de.

Organisation: 
Job location: 
Chair for Mathematics of Information Processing
RWTH Aachen University
52062 Aachen
Germany
Contact and application information
Deadline: 
Tuesday, February 26, 2019
Contact name: 
Holger Rauhut
Categorisation