University Professorship at KIT (W3) „Robust and Efficient AI“ (f/m/d)

University Professorship at KIT (W3) „Robust and Efficient AI“ (f/m/d)

Eggenstein-Leopoldshafen Vollzeit 49500 - 60500 € / Jahr (geschätzt) Kein Homeoffice möglich
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Auf einen Blick

  • Aufgaben: Entwickle fortschrittliche KI-Modelle und optimiere Algorithmen für Hochleistungsrechner.
  • Unternehmen: KIT, eine führende Forschungsinstitution mit innovativer Umgebung.
  • Vorteile: Exzellente Forschungsbedingungen, internationale Netzwerke und familienfreundliche Angebote.
  • Weitere Informationen: Klare Karrierewege und individuelle Entwicklungsmöglichkeiten warten auf dich.
  • Warum dieser Job: Gestalte die Zukunft der KI und arbeite an spannenden interdisziplinären Projekten.
  • Qualifikationen: Erfahrung in der Forschung zu robuster und effizienter KI sowie Lehrfähigkeiten.

Das prognostizierte Gehalt liegt zwischen 49500 - 60500 € pro Jahr.

Artificial intelligence offers tremendous opportunities, but at the same time it also creates significant challenges — particularly due to the rapidly rising computing demands.

Robustness, scalability, and efficiency of AI methods are therefore essential goals of AI research.

At KIT, the Scientific Computing Center (SCC) and the Division II with the KIT Department of Informatics and the Institute for Anthropomatics and Robotics (IAR) address these strategically important issues while in particular focusing on interdisciplinary application scenarios in mind, and on this basis are establishing a

  • Your Tasks
  • Research: Your work focuses primarily on developing state-of-the-art AI models for scientific applications, optimizing AI training algorithms for efficient deployment on high-performance computing (HPC) systems, creating large-scale probabilistic models and scalable methods for uncertainty quantification to achieve robust AI.

Your research methodology is both generic and application-oriented.

  • Teaching: You will teach two semester hours per week in the bachelor’s and master’s computer science programmes.

Your teaching offerings are generally also of interest to students from other engineering, natural-science, and interdisciplinary degree programs.

  • Governance: You will take on the position of a head of department within the central scientific unit SCC as part of the Helmholtz Program Engineering Digital Futures (EDF).

Your Profile

  • Your research profile aligns with the topic “Robust and Efficient Scalable AI for Science,” and you intend to strongly advance this field at KIT with great commitment.
  • You have both generic and application-oriented research experience, which you can demonstrate, for instance, through competitively funded projects at the interdisciplinary interface between computer science and applied sciences.

Employment is subject to Art. 14, par. (2) of the KIT Act in conjunction with Art. 47 LHG Baden-Württemberg (Act of Baden-Württemberg on Universities and Colleges).

  • We Offer
  • Excellent Research Conditions & State-of-the-art Infrastructure : Benefit from a unique environment that combines university and large-scale research, and gain access to state-of-the-art equipment and interdisciplinary projects.

This environment enables you to conduct both basic and applied research at the highest level.

  • International Networking : You will work in a global network that encompasses international collaborations and English-language scientific communication.

KIT promotes exchange with leading research institutions and industry partners worldwide.

  • Transparent Career Paths & Personal Development : Clear development prospects, individual coaching, and a well-developed leadership development program support you in steering your academic career in a targeted manner.
  • Family-friendly Offers : The KIT Dual Career Service supports you and your partner in integrating into the workforce, while flexible working time models and company childcare facilities make it easier to balance work and family life.
  • Onboarding & Integration : A customized onboarding program will accompany you from your first day at work, enabling you to quickly get started in research, teaching, and the KIT networks and get off to the best possible start.
  • Salary

Salary is governed by the statutory provisions of the State of Baden-Württemberg and comprises the basic salary of salary grade W3.

In addition, the granting of performance-related pay components is possible.

The family allowance is paid, where applicable, in accordance with civil service law.

  • Contact Person in line-management
  • For subject-matter inquiries, please contact Prof. Dr. Bernhard Beckert, email:
  • Application

At KIT we value the diversity of our employees; different perspectives and backgrounds enrich our work.

We therefore welcome applications from all candidates.

Women are especially encouraged to apply.

Applications from recognized severely disabled individuals are given preferential consideration when qualifications are equal.

  • Application up to: 2026-08-31
  • Job posting number: 1186/2026
  • KIT processes your personal data in accordance with this
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University Professorship at KIT (W3) „Robust and Efficient AI“ (f/m/d) Arbeitgeber: Karlsruhe Institute of Technology (KIT)

Das KIT bietet eine herausragende Forschungsumgebung mit modernster Infrastruktur und Zugang zu interdisziplinären Projekten, die es Ihnen ermöglichen, Ihre Karriere im Bereich der Forschung Software Engineering voranzutreiben. Die transparente Karriereentwicklung, individuelle Coaching-Möglichkeiten und familienfreundliche Angebote wie flexible Arbeitszeiten und Betreuungsangebote machen das KIT zu einem attraktiven Arbeitgeber. Zudem fördern wir internationale Netzwerke und bieten Unterstützung bei der Einarbeitung, um Ihnen den Einstieg in Forschung und Lehre zu erleichtern.

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Kontaktdaten:

Karlsruhe Institute of Technology (KIT) Recruiting-Team

Wir glauben, dass du diese Fähigkeiten brauchst, um University Professorship at KIT (W3) „Robust and Efficient AI“ (f/m/d) mit Bravour zu bestehen

Entwicklung von KI-Modellen
Optimierung von KI-Trainingsalgorithmen
Hochleistungsrechnen (HPC)
Erstellung probabilistischer Modelle
Skalierbare Methoden zur Unsicherheitsquantifizierung
Interdisziplinäre Forschungserfahrung
Lehre in Informatikprogrammen