| Location: | Bayreuth, Germany |
| Job Type: | Full-Time |
| Employer: | University of Bayreuth |
We are looking for an internationally outstanding scholar who will establish an independent research and teaching profile at the interface between computer science and the natural and life sciences. Applicants who combine artificial intelligence methods such as Convolutional Neural Networks or Deep Learning with biological/medical image and signal processing, for example in the fields of multimodal imaging or feedback-controlled microscopy, are particularly welcome. In particular, cooperation with the future Medical Campus Upper Franconia, the Transregional Collaborative Research Centre SFB/TRR 225 ‘From the fundamentals of biofabrication towards functional tissue models' and the Collaborative Research Centre (SFB) 1357 'Microplastics', as well as other future collaborative initiatives is expected.
The postholder will be involved in the teaching of computer science courses and courses in the natural and life sciences. The ability to teach in English is a prerequisite for employment, as significant parts of the teaching programme are offered in English; international applicants must be willing and able to teach in German, at least in the medium term.
The general administrative requirements for hiring professors at universities in Bavaria apply. A complete description of the vacancy can be found at https://uni-bayreuth.de/en. Applications (CV, outlining education and academic career, list of publications, list of courses taught, experience obtaining external funding, as well as copies of all diplomas and certificates) are to be submitted electronically to the Dean of the Faculty of Mathematics, Physics & Computer Science Prof. Dr. Volker Ulm via https://uni-bayreuth.berufungsportal.de by 16.01.2022. Applicants are welcome to direct questions and requests for further information to the Dean at This email address is being protected from spambots. You need JavaScript enabled to view it.. Application documents will be deleted in accordance with data protection law following conclusion of the appointment process.