Navigation

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)

The Chair of Digital Health at FAU Erlangen-Nürnberg invites applications for the post of 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)

Das Aufgabengebiet umfasst u. a.

The successful candidate will conduct research in wearable and IoT sensor systems design and machine learning methods for 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 in a dedicated PhD programme. Educational activities, including projects and seminar 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.

Notwendige Qualifikation

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: embedded electronics, 3D CAD, digital fabrication, or machine learning. 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.

Bemerkungen

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.

Bewerbungsschluss
15.05.2021

Detailinformationen

Stellenbezeichnung
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)
Besetzung zum
01.07.2021

Entgelt
TV-L E13 (je nach Qualifikation und persönlichen Voraussetzungen)
Teilzeit / Vollzeit
Vollzeit
Befristung
3-4 years

Kontaktperson für weitere Informationen
Prof. Dr. Oliver Amft
Telefon: +49 9131 85-23601
E-Mail: oliver.amft@fau.de
Lehrstuhl für Digital Health
Henkestr. 91, Geb. 7
91052 Erlangen Bayern
Übersicht

Für alle Stellenausschreibungen gilt: Die Friedrich-Alexander-Universität fördert die berufliche Gleichstellung der Frauen. Frauen werden deshalb ausdrücklich aufgefordert, sich zu bewerben.

Schwerbehinderte im Sinne des Schwerbehindertengesetzes werden bei gleicher fachlicher Qualifikation und persönlicher Eignung bevorzugt berücksichtigt, wenn die ausgeschriebene Stelle sich für Schwerbehinderte eignet. Details dazu finden Sie in der jeweiligen Ausschreibung unter dem Punkt "Bemerkungen".

Bei Wunsch der Bewerberin, des Bewerbers, kann die Gleichstellungsbeauftragte zum Bewerbungsgespräch hinzugezogen werden, ohne dass der Bewerberin, dem Bewerber dadurch Nachteile entstehen.

Ausgeschriebene Stellen sind grundsätzlich teilzeitfähig, es sei denn, im Ausschreibungstext erfolgt ein anderweitiger Hinweis.