Professor (m/w/d) für Generative AI (Open Rank: W3 oder W2 mit Tenure Track zu W3)

University of Technology Nuremberg Nürnberg

Stellenbeschreibung:

Join to apply for the Professor (m/w/d) für Generative AI (Open Rank: W3 oder W2 mit Tenure Track zu W3) role at University of Technology Nuremberg .

Overview

Die Technische Universität Nürnberg (UTN), gegründet im Jahr 2021, ist ein dynamisches Experimentierfeld für die Universität der Zukunft – angepasst an das Zeitalter der Künstlichen Intelligenz sowie an den ständigen technologischen, wirtschaftlichen und gesellschaftlichen Wandel. Mit dem Ziel, eine führende internationale Institution mit einem Schwerpunkt auf Künstlicher Intelligenz zu werden, setzt die UTN gleichermaßen auf Exzellenz in Forschung, Lehre und Transfer. Die UTN verfügt über eine schlanke Governance-Struktur, einen 37 Hektar großen Campus, teilweise als Wohncampus genutzt, und dient als Herzstück eines neuen Stadtteils in Nürnberg, unweit der historischen Altstadt. Dort werden künftig rund 6.000 Studierende von etwa 200 Professorinnen und Professoren sowie zahlreichen wissenschaftlichen und administrativen Mitarbeitenden betreut. Durch interdisziplinäre Zusammenarbeit, Forschung in thematischen Aktivitätsfeldern und ein internationales Netzwerk fördert die UTN Spitzenleistungen und Talente. UTN legt großen Wert auf eine offene und integrative Kultur, in der sich jeder willkommen fühlt. Die Metropolregion Nürnberg gehört zu den innovativsten Regionen der EU, überzeugt mit erschwinglichen Lebenshaltungskosten, hoher Lebensqualität und einer naturnahen Stadtkultur.

Responsibilities

Represent the field of Generative AI in research and teaching and play a central role in developing the new Department of Computer Science & Artificial Intelligence (CSAI).
Collaborate with leading international scientists in computer science and artificial intelligence and pursue interdisciplinary projects across CSAI and other departments at UTN.
Demonstrate strong practical relevance and visibility of research, contribute to the university’s public outreach and provide supervision for theses and doctoral projects.
Engage in interdisciplinary third‑party funding applications and support the development of English‑taught study programmes, curriculum development, and innovative digital teaching and learning concepts.
Actively contribute to the building phase of UTN, embrace the innovative department structures and promote diversity and gender equality in academia.

Qualifications

Open rank: W3 or W2 with Tenure Track to W3, suitable for early‑career researchers with strong potential as well as established scientists with proven excellence.
Outstanding qualifications and broad expertise in Generative AI, e.g., large language models, training and inference optimization, vision language models, vision language action models, generative audio models, foundation models for robotics, generative tactile models, multimodal generative AI, and issues of privacy, responsibility and trustworthiness in foundation models.
For a W2 Tenure‑Track position, demonstrate academic excellence through relevant publications, initial success in raising external funding, and experience in teaching and supervising student theses or doctoral research.
For a W3 position, demonstrate substantial achievements that reflect academic excellence, pedagogic and leadership capabilities, including international recognition, interdisciplinary research successes, significant success in raising competitive research funding, proven ability to manage research groups and extensive teaching and supervisory experience.
Open to UTN’s innovative department structures, actively embrace diversity and gender equality, bring sensitivity to inclusivity issues, and possess an internationally oriented academic experience.

Application Requirements

Reference number: PF- .
Submit application by January 31, 2026.
Provide all documents in English: cover letter, CV (including externally funded projects and awards), publication list, research statement, teaching statement (referencing UTN’s innovative teaching and learning concept), degree certificates, doctoral certificate (if applicable), any other relevant credentials, and four publications that best represent your research profile.
Submit exclusively via the UCN online application portal.
Guidelines for preparing the teaching statement: Word format: , PDF format: .

Equal Opportunity Statement

The Technische Universität Nürnberg is an inclusive university that offers knowledge and equal opportunities to people regardless of gender, age, sexual orientation, ideology, religion, origin or disability. The position is suitable for severely disabled persons. Severely disabled applicants will be given preference if their suitability, qualification and professional performance are otherwise essentially equal. Family‑friendliness is the basis for achieving equal opportunities for men and women in science. Therefore, we offer flexible ways of working, family‑friendly times for events and meetings, as well as dual‑career options.