Professor (m/f/d) (Open Rank: W3 or W2 with Tenure Track to W3) of Generative AI

at the department Computer Science & Artificial Intelligence

Your tasks:

You represent the field of Generative AI in both research and teaching and play a central role in developing the new Department of Computer Science & Artificial Intelligence (CSAI). You are expected to collaborate with leading international scientists in computer science and artificial intelligence and to perform interdisciplinary projects together with researchers across CSAI and other departments at UTN. Your research should demonstrate strong practical relevance and visibility, complemented by active contributions to the university’s public outreach. In addition, you will engage in interdisciplinary third-party funding applications and provide supervision for theses and doctoral projects.

Your profile:

These positions are open to both early-career researchers with strong potential for academic growth as well as established scientists with a proven record of excellence.
Candidates are expected to demonstrate outstanding qualifications and broad expertise in Generative AI, for example 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, as well as issues of privacy, responsibility, and trustworthiness in foundation models.
Assistant professor (W2 tenure track) candidates should demonstrate academic excellence through relevant publications and initial success in raising external funding. Experience in teaching and supervising student theses or doctoral research is expected.
Full professor (W3) candidates must show substantial achievements that reflect academic excellence as well as pedagogical and leadership capabilities. This includes international recognition in their field, proven achievements in interdisciplinary research, significant success in raising competitive research funding, proven ability to manage research groups, and extensive teaching and supervisory experience, including completed doctoral supervisions.
At both career stages, we are seeking individuals who are open to UTN’s innovative department structures, who actively embrace diversity and gender equality in academia, and who bring sensitivity to inclusivity issues. An internationally oriented academic experience is desired. We are looking for team players willing to embrace something new and actively shape our university.
Successful candidates will be expected to contribute to the department’s current and future English-taught study programs, participate in curriculum development, and engage in the implementation of innovative digital teaching and learning concepts. A willingness to collaborate both within the department and across disciplinary boundaries is essential.
Legal criteria for hiring are defined in Articles 57 (1) and 60 (3) of BayHIG. Accordingly, applicants must hold a completed university degree, demonstrate pedagogical and personal aptitude, and have proven their ability for independent research, typically evidenced by a doctoral degree and additional academic accomplishments.

Our offer

The University of Technology Nuremberg is rethinking the university on all levels. We offer a motivated and excellent international team in which you can contribute with all your ideas and competencies. You will be able to experience and develop new, interdisciplinary forms of research collaboration as well as teaching and learning and help us shaping them.
We will make sure that you are able to fully focus on your work by our modern, service-oriented administrative units. We see diversity as an asset. The University of Technology Nuremberg is a place that offers knowledge and equal opportunities to people regardless of gender, age, sexual orientation, ideology, religion, origin or disability. The position is suitable to be filled by severely disabled persons.
Severely disabled applicants will be given preference if their suitability, qualification, and professional performance are otherwise essentially equal. We see family-friendliness as 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. The University of Technology Nuremberg aims at increasing the proportion of women in research and teaching and therefore strongly encourages women to apply.

Interested?

Please refer to the reference number PF-2025-07 in your application. Applications must be submitted by January 31, 2026, including all relevant documents in English: cover letter, CV (including externally funded projects and awards), publication list, research statement, teaching statement (referencing our innovative UTN teaching and learning concept), degree certificates, doctoral certificate (if applicable), and any other relevant credentials, as well as four publications that best represent your research profile. Applications should be submitted exclusively via our online application portal. Guidelines for preparing the teaching statement can be found at the following links:

Questions?

If you have any administrative questions, please contact the Appointments Team, appointments@utn.de.
If you have questions regarding the profile of the position, please contact the Founding Chair of the Department of Computer Science & Artificial Intelligence, Prof. Dr. Wolfram Burgard, wolfram.burgard@utn.de.

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"Professor (m/f/d) (Open Rank: W3 or W2 with Tenure Track to W3) of Generative AI"

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