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

University of Technology Nuremberg; Deutschland; Vor Ort; EUR 70.000 - 100.000; Vollzeit

Zusammenfassung

A leading university in Germany seeks to fill two positions for a Professor of Generative AI in the Department of Computer Science & Artificial Intelligence. Candidates should have expertise in Generative AI, demonstrated teaching capabilities, and interest in interdisciplinary research. This role includes representing the field, engaging in funding applications, and supervising projects. The university values diversity and welcomes applications from candidates of all backgrounds, providing a supportive environment for professional growth.

Leistungen

Flexible working arrangements

Family-friendly policies

Diversity and inclusion initiatives

Qualifikationen

• Candidates must demonstrate outstanding qualifications and broad expertise in Generative AI.
• Experience in teaching and supervising student theses or doctoral research is required.
• Internationally recognized achievements in the field are essential for full professor candidates.

Aufgaben

• Represent the field of Generative AI in research and teaching.
• Collaborate with international scientists and participate in interdisciplinary projects.
• Engage in third-party funding applications and supervise doctoral projects.

Kenntnisse

Generative AI

Large language models

Interdisciplinary research

Teaching experience

Fundraising for research

Ausbildung

Doctoral degree

Jobbeschreibung

Organisation/Company University of Technology Nuremberg Department CSAI Research Field Computer science » Informatics Researcher Profile Recognised Researcher (R2) Positions Other Positions Country Germany Application Deadline 31 Jan 2026 - 23:59 (Europe/Berlin) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number PF-2025-07 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The University of Technology Nuremberg (UTN), founded in 2021, is a living laboratory for the university of the future – adapted to the age of artificial intelligence and to constant technological, economic, and social change. Aiming to become a leading international institution with a focus on artificial intelligence, UTN is equally committed to excellence in research, teaching, and transfer. Its lean governance structure supports an agile and efficient implementation of its vision. Its sus‑tainable, 37‑hectare and partly residential campus will form the heart of a new district in Nuremberg, not far from the his‑toric old town. On its campus, around 6,000 students will learn from and work with around 200 professors and numerous academic and administrative staff. The academic organization of UTN is based on Departments as central structural units. The Departments of Computer Science & Artificial Intelligence and of Liberal Arts & Social Sciences are already estab‑lished. Three further Departments are in development: Biological Engineering, Mechatronic Engineering, and Natural Sciences. Departments at UTN are characterized by flat hierarchies and offer exciting opportunities for challenging and re‑warding career paths. UTN attaches great importance to interdisciplinary cooperation, such as interdisciplinary research on themes for which research outputs can bring about major benefits to our society and its economy. Most degree programs at UTN are offered in English. German and English are the languages of work in administration, teaching, and research, while the official and legal language is German. Digital technologies, AI, and innovative applications are used in a targeted man‑ner to improve university life and work experience for everyone. UTN is characterized by an open and inclusive culture where everyone feels welcome. Diverse backgrounds, perspectives, and experiences of staff, students, and stakeholders help to achieve excellence and develop talent. The Nuremberg Metropolitan Region is one of the most innovative regions in the EU. It impresses with affordable living costs, a high quality of life, and an urban culture close to nature. It also offers an excellent regional transport network and optimal connections to European travel routes and international transport hubs in Germany.
The University of Technology Nuremberg is looking to fill, at the earliest possible date, up to two positions as a

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:

• Word: https://www.utn.de/files/2022/11/UTN-Teaching-Statement-DE.docx

Questions?

If you have any administrative questions, please contact the Appointments Team, [e-mail] .
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, [e-mail] .
You can find more information on our data privacy policy at https://www.utn.de/en/privacy/ .