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Research Group Leader – Machine Learning and Human-Computer Interaction. Full time, remuneration according to TV-L Bavaria E14 scale and regulations.

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

Research Group Leader – Machine Learning and Human-Computer Interaction. Full time, remuneration according to TV-L Bavaria E14 scale and regulations.

Das Aufgabengebiet umfasst u. a.

The successful candidate will conduct fundamental and applied research in artificial intelligence and machine learning related to biomedical models and simulation, as well as human interaction with computer models in virtual/augmented reality. The candidate may pursue a habilitation thesis within approx. four years of appointment and is offered a path to a permanent, tenure appointment upon attaining previously negotiated achievements. The responsibilities will include:

  • Establish a strong research track in the field of machine learning for biomedical modelling and human-computer interaction with computer-based models.
  • Establish successful collaborations with different institutes and chairs at FAU and the UH Erlangen, as well as with national and international partners.
  • Guide and advise students at all levels, including bachelor, master, and Ph.D.
  • Develop proficiency in research funding acquisition.

Notwendige Qualifikation

We look for a candidate with a strong expertise in artificial intelligence and human-computer interaction paired with the interest in explainable systems and biomedical modelling, e.g. through previous research in computer vision and/or virtual/augmented reality. The position is suitable for both a young researcher, who is completing the Ph.D. as well as for a more senior academic. Educational background should be in computer science, electrical engineering, medical engineering, or related discipline. The successful candidate should have published in international scientific journals already. A university degree and doctoral degree (Ph.D.), pedagogical aptitude, and proficient English language skills are prerequisites for this position. Good command of German or documented aspiration to acquire the German language is a plus.

Bemerkungen

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

Please send your application in English language, including a cover letter with interests and background (max. 1 page), 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. As the chair offers multiple positions, please denote the intended opening in the e-mail subject line: ‘Research Group Leader Machine Learning and Human-Computer Interaction’.

Applications sent via e-mail will be confirmed within a week. Please note that applications not complying with the above requirements may neither be confirmed not considered.

Please note that the candidate evaluation involves one or more scientific-technical presentations and interview appointments to be held via teleconferencing. Candidate selection is done based on scientific qualification, specific professional experience in the described research fields, past experience in guiding Ph.D. candidates, and individual development potential.

Bewerbungsschluss
15.05.2021

Detailinformationen

Stellenbezeichnung
Research Group Leader – Machine Learning and Human-Computer Interaction. Full time, remuneration according to TV-L Bavaria E14 scale and regulations.
Besetzung zum
01.10.2021

Entgelt
TVL E14 (je nach Qualifikation und persönlichen Voraussetzungen)
Teilzeit / Vollzeit
Vollzeit
Befristung
5 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

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