Full Professor of Artificial Intelligence in Physico-Chemical Material Analysis

Faculty of Biology, Chemistry and Earth Sciences

Application deadline:

The University of Bayreuth is a research‐oriented university with internationally competitive, interdisciplinary focus areas in research and teaching. The Faculty of Biology, Chemistry & Earth Sciences at the University of Bayreuth is currently seeking to appoint a

Full Professor of Artificial Intelligence in Physico-Chemical Material Analysis

at salary grade W 3 to commence as soon as possible. This is a permanent civil service position. Secondary membership in the Faculty of Mathematics, Physics & Computer Science is envisaged.

We are looking for a dynamic and creative scholar with a visible profile at the interface between experimental materials analytics and computational data science. The successful applicant will have a proven record in the following areas of materials analytics and data science:

  • Quantitative analysis of condensed matter, especially structured or hybrid systems.
  • Use of data from analytical techniques such as optical spectroscopy, NMR spectroscopy, impedance spectroscopy, scattering methods, or imaging methods
  • Knowledge-based methods of machine learning or pattern recognition for regression or classification problems


Active involvement in the focus areas Polymer & Colloid Science, Advanced Materials, as well as existing and planned research networks is expected. Close interaction with materials research groups within the framework of the Bavarian Polymer Institute, the North Bavarian NMR Centre, the Bayreuth Centre for Colloids and Interfaces and, in particular, the Bavarian Centre for Battery Technology is expected. Furthermore, the professorship is to be involved in the Bayreuth Centre for Artificial Intelligence as well as the AI Network Bavaria.

Teaching contributions are expected in the undergraduate teaching of the relevant chemistry degree programmes. In particular, the professorship is expected to develop lectures, seminars, and practical courses on the foundations and applications of artificial intelligence in the field of materials science, as well as on data evaluation, in both the bachelor's and master's programmes, and to contribute to the teaching exported to related and interfaculty degree programmes. The ability to teach in English and, in due course, in German is expected.

In addition to the general legal requirements, prerequisites for this position are a university degree, a doctoral degree, proven excellence in teaching, and a post-doctoral qualification to teach at a professorial level (Habilitation). Alternatively, evidence of equivalent scholarly achievement, for example as a junior professor or in a non-university environment, will also be considered.  Only applicants who are 51 years of age or younger can be hired as civil servants. Exceptions will be made if there are urgent reasons for doing so (Art. 10 Abs. 3 BayHschPG).

The University of Bayreuth views the diversity of its staff as an asset and is expressly committed to the goal of gender equality. Female scholars and any persons who can help make the research and teaching profile of the university more diverse are strongly encouraged to apply. Applicants with children are highly welcome. The University of Bayreuth is a member of the best practice club Family at University, and it offers “dual career support” for career-oriented partners of highly qualified employees. In addition, an extended audit conducted by the German Rectors’ Conference (HRK) returned a favourable review for the University of Bayreuth’s commitment to internationalization. All qualifications being equal, applicants with disabilities will be given priority.

Applications (CV including a list of publications, list of courses taught, experience obtaining external funding, as well as copies of certificates and diplomas) are to be addressed to Prof. Dr. Benedikt Westermann, Dean of the Faculty of Biology, Chemistry & Earth Sciences and submitted via https://uni-bayreuth.berufungsportal.de by 12.10.2022. Applicants are welcome to direct questions and requests for further information to the Dean at dekanat.bcg@uni-bayreuth.de. Application documents will be deleted in accordance with data protection law following the conclusion of the appointment process.