The Faculty of Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) invites applications for an
Open Topic Tenure Track Professorship for Data, Sensors and Devices / Digital Transformation (W1 / Assistant Professor)
at the Department of Artificial Intelligence in Biomedical Engineering
Candidates should have already developed their own teaching and research profile, particularly in the following areas: We seek to appoint a top early career scientist who will develop outstanding expertise in the field of artificial intelligence in biomedical engineering focusing on data, sensors and devices/digital transformation.
The professorship is part of the Federal and State programme for supporting young researchers and is to be filled by the earliest possible starting date for an initial period of three years. Upon successful evaluation, the appointment will be extended for another three years. FAU offers the long-term perspective of a permanent appointment to a W3 professorship if the requirements of the tenure evaluation are met.
- Human-technology interaction (e.g. intelligent multimodal medical UI, smart scanning support, brain-computer interface, neuromonitoring)
- Autonomous and intelligent data acquisition (e. g. automated quality assurance, smart examination, scan optimisation)
- Data integration, representation and visualisation (e. g. knowledge representation, smart research data management/semantic interoperability, process optimisation, process mining)
- Computational methods for bioinformatics (e. g. artificial intelligence for analytics, -omics, computational neuroscience)
- Intelligent materials and sensors (e. g. sensory/biosensory materials, intelligent sensing, sensing and analysis of human motion and emotion, lab on a chip for digital diagnostics, neuromorphic circuits)
Successful candidates must be willing to collaborate in setting up and teaching a new Bachelor’s and Master’s degree programme in Artificial Intelligence in addition to teaching in existing degree programmes such as Medical Engineering, Medical Process Management and Data Science. The professor will be appointed as a member of the Faculty of Medicine and the Faculty of Engineering.
For further information and the application guideline please see