Postdoc / Senior Researcher in Machine Learning for Biomedical Sensor Data
The Chair of Digital Health at FAU Erlangen-Nürnberg invites applications for the position of a
Postdoc / Senior Researcher –
Machine Learning for Biomedical Sensor Data.
Full time, remuneration according to TV-L Bavaria E13/A13 or E14/A14 scales and regulations (min. starting salary ~63’241 €/year).
The successful candidate will conduct fundamental and applied research in machine learning methods related to biomedical sensor data modelling, simulation and personalised medicine. Illustrations of potential research directions can be found at the chair’s website and publications; other research directions are possible too. The successful candidate will work on and contribute to scientific publications in top-ranked journals. 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 intelligence for biomedical sensor data modelling, simulation and personalised medicine.
- 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.
We look for a candidate with expertise in artificial intelligence methods and biomedical sensor data. The position is suitable for a young researcher, who is completing the Ph.D., but can accommodate a senior academic too. 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 (anticipated) 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.
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 to support 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.
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 € (2016) third-party funding, and 500 partnerships with universities all over the world. University teaching is closely linked to research and focuses on training students in both theory and practice to enable them to think critically and work independently. 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 and the Chair of Digital Health can be found online: FAU, Chair of Digital Health.
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: ‘Postdoc / Senior Researcher Machine Learning for Biomedical Sensor Data’.
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.
If you have questions regarding this position offer, please contact Prof. Dr. Oliver Amft.