"PhD or Post-Doc Candidate (m/f/x)"

Institution Faculty of Mathematics, Informatics and Statistics - Mathematisches Institut

Remuneration group TV-L

Full-time / Part-time Full-time (100%)

Start date starting from now (for two years, with an option of contract extension)

Application deadline 2024-09-01

About us:

The Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence is a newly founded AI Chair at the Mathematical Institute of the Faculty of Mathematics, Computer Science and Statistics at the Ludwig-Maximilians-Universität München and is part of the HighTech Agenda of the Free State of Bavaria. One main focus of our research is on the development of mathematical foundations and the analysis of key approaches of artificial intelligence such as deep neural networks. We also introduce and study reliable AI-based algorithms in the field of inverse problems and partial differential equations, aiming at applications in medical image processing, robotics, and telecommunication. Furthermore, our chair is responsible for various major initiatives at the LMU as well as in the strong Munich AI Ecosystem, such as the AI-HUB@LMU and the Konrad Zuse School of Excellence in Reliable AI.

The advertised position is part of the project "Spiking Neural Networks: Theoretical Foundations, Trustworthiness, and Energy-Efficiency", which is being carried out in cooperation with Prof. Dr. Boche (Chair for Theoretical Information Theory, Technical University of Munich). Spiking neural networks model the human brain much better than classical neural networks, in particular with the aim of solving the enormous energy problem and problems with the trustworthiness of current AI. In this project, their mathematical foundations are to be developed, particularly concerning reliability and energy efficiency. The project is part of the DFG priority program SPP 2298 "Theoretical Foundations of Deep Learning".

We are looking for you:

PhD or Post-Doc Candidate (m/f/x)

in Munich

Your tasks and responsibilities:

• Research on the questions of the project "Spiking Neural Networks: Theoretical  Foundations, Trustworthiness, and Energy-Efficiency"
• Publication of research results in national and international journals
• Presentation of research results at international conferences
• Participation in the events of the SPP 2298.

Your qualifications:

• You have a very good university degree in mathematics, computer science, or a comparable subject, preferably focusing on the mathematical foundations of artificial intelligence and/or image processing/inverse problems
• You have good programming skills
• Your communication in German and English is business fluent, both written and spoken.

Benefits:

• A highly topical field of research
• The opportunity to network uniquely with the German interdisciplinary research community in the field of the theoretical foundations of deep learning through various events of the SPP 2298
• An inspiring, collegial working atmosphere in a highly international research group
• The opportunity to do a doctorate
• A workplace in a central location in the beautiful city of Munich that is easily accessible by public transport.

Remuneration is based on appropriate qualifications and professional experience up to TV-L E13.

The University of Munich endeavours to increase the proportion of women among its academic staff and expressly encourages qualified women to apply.

Also possible in a part-time capacity.

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

Contact:

We look forward to receiving your application by e-mail (one PDF, maximum 5MB) with the usual documents (cover letter, CV, copies of certificates, list of publications, contact details for two references) by 01.09.2024 to Prof. Dr. Gitta Kutyniok, skr101@math.lmu.de.

Please contact Prof Dr Gitta Kutyniok (kutyniok@math.lmu.de) if you have any questions.

Where knowledge is everything.

LMU researchers work at the highest level on the great questions affecting people, society, culture, the environment and technology — supported by experts in administration, IT and tech. Become part of LMU Munich!

In the course of your application for an open position at Ludwig-Maximilians-Universität (LMU) München, you will be required to submit personal information. Please be sure to refer to our LMU Privacy Policy. By submitting your application, you confirm that you have read and understood our data protection guidelines and privacy policy and that you agree to your data being processed in accordance with the selection process.