Your browser is outdated. We recommend an update or using another browser to visit our website.


W3-Professorship for Intelligent Energy Management

Faculty of Engineering Science

Application deadline:

The University of Bayreuth is a research-oriented university with internationally competitive and interdisciplinary focus areas in research and teaching. The University of Bayreuth has a vacancy in the Faculty of Engineering Science for a

W3-Professorship for Intelligent Energy Management

with tenure as a civil servant.  

The successful applicant will represent the field of artificial intelligence for electrical grids and distributed energy systems in research and teaching, and already have an excellent track record in relevant engineering work.  

The research focus should cover the topics of "energy management, electrical grids, and distributed energy systems". In addition, they will have one further focus in each of the two following areas.

In the area of algorithms:

  • Machine learning methods: descriptive, predictive, and prescriptive learning
  • AI methods of planning and optimisation for distributed systems and complex topologies  

and in the area of technical implementation: 

  • Software and hardware concepts for real-time control and regulation of distributed systems
  • Data acquisition and communication electronics for the "Internet of Things"

In teaching, the professorship is tasked with representing the fundamentals and specialisations of the methods of artificial intelligence and electrical networks and, in doing so, contributing significantly to the further development of the Electrical Engineering & Information Systems Technology degree programme.  

The future chair is expected to be willing to take on a research orientation complementary to the existing research groups in the Faculty of Engineering Science, especially in the Centre for Energy Technology, in the Bayreuth Center for Artificial Intelligence, and in the AI Network Bavaria, and to participate in interdisciplinary research both within the faculty, across faculty boundaries in the profile field of energy research and energy technology, with the Bavarian Centre for Battery Technology (BayBatt), and in the context of the AI Network Bavaria.  

The ability to teach in German and English is required.  

In addition to the general requirements under civil service law, the prerequisites for employment are a completed university degree, pedagogical aptitude, and a special aptitude for scientific work, as demonstrated by an outstanding doctorate, and a habilitation or equivalent scientific achievements, which may also have been achieved in the context of a junior professorship or outside the university sector. According to the Bavarian legal regulations, anyone who has not yet reached the age of 52 may be appointed to civil service. Exceptions are possible in urgent cases (Art. 10 Para. 3 BayHschPG).  

The University of Bayreuth considers diversity among its employees an enrichment, and is expressly committed to the goal of gender equality. Female academics are thus expressly encouraged to apply in this regard. Persons who bring more diversity to the research and teaching profile of the University of Bayreuth are expressly invited to apply. Applicants (m/f/d) with children are very welcome. The University of Bayreuth is a member of the Best Practice Club "Familie in der Hochschule e.V.", has successfully participated in the HRK "Internationalisation of Higher Education" audit, and offers Dual Career Support. Persons with severe disabilities will be given preferential consideration if they are equally qualified.   

Applications (curriculum vitae with list of publications, teaching experience, third-party funding, certificates, and diplomas) are requested by 13 February 2022 and should be submitted to the Dean of the Faculty of Engineering Science, Prof. Dr. Ruth Freitag and at The Dean is available for questions and further information at All application documents will be deleted after the end of the appointment procedure in accordance with the requirements of data protection.