PhD Student

Vor 2 Tagen


Ingolstadt, Bayern, Deutschland MathHire Vollzeit 24.478 € - 35.435 € pro Jahr

The research group Reliable Machine Learning at the KU Eichstätt-Ingolstadt is seeking highly motivated candidates for a part-time position (75%) at the next possible date as a

PhD Student (m/f/d)

with contract duration of 3 years. The place of work will be in Ingolstadt. The salary is prescribed by the framework of the collective agreement (TV-L), Level 13 (75%).

The research group Reliable Machine Learning (headed by Prof. Felix Voigtlaender) is part of the Mathematical Institute for Machine Learning and Data Science (MIDS) at the KU Eichstätt-Ingolstadt and is funded by the High-Tech Agenda of Bavaria. The advertised position is funded via the Emmy Noether project "Stability and Solvability in Deep Learning". This project focuses on mathematically analyzing machine learning algorithms with a particular focus on questions of stability, computability, and robustness of methods from Deep Learning.

Your tasks

  • Contribution to the research project "Stability and Solvability in Deep Learning", where your research will be a part of your dissertation
  • Knowledge transfer via publications and via participation in conferences

Your profile

  • Master's degree (or equivalent degree) in mathematics, preferably with a focus on one of the following topics:

o Machine learning

o (High-dimensional) probability theory

o Real and functional analysis

o Information-based complexity

The master's degree may still be in the process of completion at the time of application, but the degree must be completed at the start of the position.

  • Interest in mathematical analysis of machine learning algorithms
  • Practical experience in programming and machine learning (desirable but not mandatory)
  • German language skills are not required, but candidates are encouraged to develop those during their employment at the KU.

Our offer

  • Possibility to pursue own research interests and obtain a PhD in mathematics
  • Attractive and team-oriented workplace in a modern university environment
  • Interesting, responsible, and versatile range of tasks
  • International contacts