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

LMU; München; On-site; EUR 52,000 - 68,000; Full time

Benefits offered by this job

Doktoratsmöglichkeit

Zentrale Lage in München

Gute Anbindung an öffentliche Verkehr

Interdisziplinäres Netzwerk

Job summary

Die Ludwig-Maximilians-Universität München sucht kandidierende PhD- oder Post-Doc-Forscherinnen und -Forscher im Bereich der mathematischen Grundlagen intelligenter Systeme. Die Stelle ist im Fachbereich Mathematik, Informatik und Statistik im Mathematischen Institut angesiedelt.

Ihre Aufgaben umfassen eigenständige Forschung zu Spiking Neural Networks, Publikationen in führenden Zeitschriften und Beiträge zu internationalen Konferenzen. Die Position bietet die Möglichkeit zur Promotion bzw.

Qualifications

• Abschluss in Mathematik, Informatik oder verwandtem Gebiet.
• Solide Programmierkenntnisse.
• Gute Englischkenntnisse (schriftlich und mündlich).

Responsibilities

• Führen Sie Forschungsarbeiten im Projekt durch.
• Veröffentlichen Sie Ergebnisse in nationalen und internationalen Fachzeitschriften.
• Stellen Sie Ergebnisse bei internationalen Konferenzen vor.
• Unterstützen Sie die Aktivitäten des SPP 2298.

Skills

Programmierskills

Englische Kommunikation

Education

Masterabschluss in Mathematik/CS

Doktorgrad (für Postdoktoranden)

Job description

About us:

The Chair for Mathematical Foundations of Artificial Intelligence (MATH4AI), led by Prof. Dr. Gitta Kutyniok at the Mathematical Institute of LMU and established under the Hightech Agenda Bayern, develops the mathematics for the next generation of AI. We are an international team of around 35 researchers from 14 countries, organized in six research clusters at the interface of mathematics and artificial intelligence.

Our research develops the mathematical foundations of AI — representation power, learning, generalization, and explainability — and turns them into reliable, sustainable, and trustworthy AI methods. Current directions range from trustworthy and explainable AI to next-generation, brain-inspired and energy-efficient AI computing, including spiking neural networks and the fundamental limits of AI. Beyond its own research, the chair leads and shapes major initiatives within the strong Munich AI ecosystem and beyond, including the AI-HUB@LMU, the Konrad Zuse School of Excellence in Reliable AI (relAI), and the Bavaria–Saxony initiative gAIn for next-generation (green) AI computing.

The Project:
The advertised position is part of the project "Spiking Neural Networks: Theoretical Foundations, Trustworthiness, and Energy-Efficiency", carried out in cooperation with Prof. Dr. Holger Boche (Chair of Theoretical Information Technology, Technical University of Munich). Spiking neural networks model the human brain more closely than classical neural networks and are a promising route to addressing two central challenges of current AI: its enormous energy demand and its limited trustworthiness. The project aims to develop the mathematical foundations of spiking neural networks, with particular emphasis on reliability and energy efficiency. It is part of the DFG Priority Programme SPP 2298 "Theoretical Foundations of Deep Learning".

Position details:

• Institution
  Faculty of Mathematics, Informatics and Statistics - Mathematisches Institut
• Remuneration group
  TV-L
• Full-time / Part-time
  Full-time (100%)
• Start date
  2027-02-01 (limited to 2028-04-30)

We are looking for you:

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

in Munich

Your tasks and responsibilities:

• Conduct research on the questions of the project "Spiking Neural Networks: Theoretical Foundations, Trustworthiness, and Energy-Efficiency"
• Publish research results in leading national and international journals
• Present research results at international conferences
• Contribute to the activities of the DFG Priority Programme SPP 2298

Your qualifications:

• An excellent university degree (Master or, for postdoctoral candidates, a doctorate) in mathematics, computer science, or a related field, ideally with a focus on the mathematical foundations of artificial intelligence and/or image processing and inverse problems
• Solid programming skills
• Business-fluent communication in English, both written and spoken (German is welcome but not required)

Benefits:

• A highly topical and impactful field of research
• Unique opportunities to network with the German interdisciplinary research community on the theoretical foundations of deep learning through the activities of SPP 2298
• An inspiring, collegial atmosphere in a highly international research group
• For PhD candidates, the opportunity to pursue a doctorate
• A workplace in a central and attractive location in Munich, easily accessible by public transport

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

Also possible in a part-time capacity.

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

Where knowledge is everything.

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Ludwig-Maximilians-Universität München
Geschwister-Scholl-Platz 1
80539 München

www.lmu.de

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