PhD position in wearable computing and machine intelligence

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The Chair of Digital Health at FAU Erlangen-Nürnberg invites applications for a

Doctoral Researcher –
Wearable Computing, Digital Modelling, and Machine Intelligence.

Full time research position starting as soon as possible, remuneration according to TV-L E13 Bavaria regulations.


Candidates must have a master’s degree in computer science and/or electrical/com­puter/biomedical engineer­ing with a strong background in one or more of the following areas, evidenced by their academic record, previous project experience, and ideally by first publications: machine learning, pattern recognition, 3D CAD and image-based reconstruction. Moreover, experience in time-series analysis and modern data inference tools (i.e. Python) is needed. Good command of German or a strong aspiration to acquire the German language are sought.

Duties and tasks

The successful candidate will conduct research in wearable and IoT sensor systems design and machine learning methods for applications in personalised medicine. Illustrations of potential directions can be found at the chair’s website and publications. The successful candidate will work on and contribute to scientific publications in leading journals of the field. The candidate should defend their thesis within three to four years of doctoral research at the chair.

The position is intended to allow the candidate to further develop her/his scientific, technical, management and transferable skills, both on-the-job and through a personal training programme. Educational activities, including guidance of undergraduate and (post-) graduate students and contributing to teaching in accordance with the appointment regulations will contribute to career and complementary skills development.

The Chair of Digital Health

The Chair of Digital Health offers an open-minded, international working environment with an inspiring bandwidth of research projects, spanning topics in advanced data science, 3D computer modelling, biomedical signal processing, and embedded systems engineering. The chair offers collaborative projects with various medical institutes in Erlangen, Germany, and worldwide. The chair collaborates with various leading industrial/business partners too and specifically supports spin-offs. Students with various educational backgrounds consider the chair for internships and theses projects, including but not limited to computer science, medical engineering, electrical engineering, mechanical engineering, and medicine. The chair offers state-of-the-art laboratory facilities and staff supporting validation studies, including electronics development, additive manufacturing, and photometric systems. Moreover, the chair operates a dedicated computing cluster infrastructure for simulations and testing of methods and algorithms. More information on the Chair of Digital Health can be found online: Chair of Digital Health.

The University

Founded in 1743, FAU has a rich history. It is a strong research university with an international perspective and one of the largest universities in Germany, with 39.868 students, 263 degree programmes, 4,000 academic staff (including over 576 professors), 177,6 million euros (2016) third-party funding, and 500 partnerships with universities all over the world. Teaching at the University is closely linked to research and focuses on training students in both theory and practice to enable them to think critically and work independently. The research strikes the perfect balance between a theoretical approach and practical application. FAU’s outstanding research and teaching is reflected in top positions in both national and international rankings. More information on FAU can be found online: FAU.


FAU is a member of the Best Practice Club ‘Family and University’ and promotes equal opportunities. Female candidates are specifically encouraged to apply. The position is open to start immediately or at a negotiated date.

Please send your application including cover letter with interests and background (max. 1 page), plus full CV and transcripts, as one PDF document via e-mail (see contact information below) to Prof. Dr. Oliver Amft, Chair of Digital Health, FAU Erlangen-Nürnberg, Henkestrasse 91, 91052 Erlangen.

Please note that the candidate evaluation involves one or more scientific-technical presentations and interview appointments to be held via teleconferencing. Applications sent via e-mail will be confirmed within a week. Furthermore, please note that applications not complying with the above requirements may neither be confirmed not considered.


If you have questions regarding this position offer, please contact Prof. Dr. Oliver Amft.

Prof. Dr. Oliver Amft

  • Job title: Director
  • Phone number: +49 9131 85-23601

Friedrich-Alexander-Universität Erlangen-Nürnberg