Catholic University Eichstaett-Ingolstadt, Mathematics

Position ID: 1778-POSTDOC1 [#19670, R2]
Position Title: Postdoc researcher
Position Type: Postdoctoral
Position Location: Ingolstadt, Bayern 85049, Germany [map]
Subject Area: Mathematics of Machine Learning
Application Deadline: 2022/04/24 11:59PMhelp popup (posted 2022/03/02, listed until 2022/09/02)
Position Description:    

The Catholic University of Eichstätt-Ingolstadt (KU) is a non-state university under church leadership and officially recognized by the Free State of Bavaria. It is committed to strong research and excellent teaching and combines first-class study conditions with an international focus. Eight faculties offer a wide range of subjects for around 5,000 students. The University employs 900 people of different faiths and beliefs. Grounded in the Christian view of human life, the KU aims to create an academic and educational culture of responsibility. 

The research group Reliable Machine Learning at the KU Eichstätt-Ingolstadt is seeking highly motivated candidates for a full-time position (100%) at the next possible date as a 
 Postdoc researcher (m/f/d) 
 with contract duration of 3 years (with possibility for extension). The place of work will be in Ingolstadt. The salary is prescribed by the framework of the collective agreement (TV-L), Level 13. The possibility of habilitation is given and is expressly desired. The newly founded research group Reliable Machine Learning (headed by Prof. Felix Voigtlaender) is part of the Mathematical Institute for Machine Learning and Data Science (MIDS) at KU Eichstätt-Ingolstadt. 
The research group is funded by the High-Tech Agenda of Bavaria, as part of the consortium Resource Aware Artificial Intelligence for Future Technologies of the KU, the FAU Erlangen-Nürnberg, the TU Munich, and the University of Bayreuth. The research of the group 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 
  • Independent mathematical research in the area of machine learning 
  • Contribution to the current research projects of the group and support in the acquisition of new research projects 
  • Participation in the development of existing and new study programs 
  • Teaching of courses related to mathematics and machine learning 
  • Knowledge transfer via publications and participation in conferences Your profile 
  • PhD in mathematics, preferably with a focus on one of the following topics:
    Machine Learning
    (High-dimensional) probability theory
    Real and functional analysis
    Information-based complexity The degree does not yet have to be complete at the date of application but must be completed when starting the position. 
  • Interest in mathematical analysis of machine learning algorithms 
  • Practical experience in programming and machine learning (highly desirable but not mandatory) 
  • Good German language skills are not required but highly desirable, since some of the courses at the University must be taught in German 

Our offer 
  • Possibility to pursue own research 
  • Possibility to gain teaching experience 
  • Attractive and team-oriented workplace in a modern university environment 
  • Interesting, responsible, and versatile range of tasks 
  • International contacts 

Your application 
Please send your application as a single PDF file containing the following: 
  • Cover letter 
  • CV 
  • List of publications (if any) 
  • (Scanned) Certificates of academic degrees (BSc, MSc, PhD, etc.), including list of courses taken and grades (for the courses during the BSc/MSc degree) 
  • Electronic copy of (or the current draft of) the PhD thesis (The PhD 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.) 
  • Letter of recommendation 
via e-mail by April 24, 2022 to Prof. Dr. Felix Voigtlaender ( Application documents submitted will be deleted after completion of the recruitment process in compliance with data protection regulations. 

All employees are obliged to acknowledge the nature and mission of the KU as stipulated in its Mission Statement and Foundation Charter. The University is therefore interested in receiving applications with relevant information in this regard. The KU is committed to promoting equal opportunities for men and women, and aims to ensure that its members are able to balance work and family life. Candidates with severe disabilities who are equally suitable to other applicants will be prioritized.

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Contact: Prof. Dr. Felix Voigtlaender
Postal Mail:
Auf d. Schanz 49
85049 Ingolstadt
Web Page: