PhD position: Wearable Computing, Digital Health, and Machine Intelligence bei Universität Freiburg

Position

The successful candidate will conduct research in wearable and IoT sensor systems design and machine learning methods for applications in personalised medicine and Digital Health. We do research on algorithms and methods that leverage sensor and interaction data to recognise context and infer complex behaviour for decision support applications. 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 lab.

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.

Qualifications

Candidates must have a master’s degree in computer science or electrical/computer/biomedical engineering, or similar, 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, timeseries analysis, 3D CAD and image-based reconstruction. Moreover, experience in modern data inference tools (i.e. Python) is needed. Good command of German or a strong aspiration to acquire the German language are sought.

About the Intelligent Embedded Systems Lab

The Intelligent Embedded Systems Lab in cooperation with Hahn-Schickard 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. We collaborate with various medical institutes and leading industrial/business partners as well as support spin-offs. Our lab members have various educational backgrounds, including but not limited to computer science, medical engineering, electrical engineering, mechanical engineering, and medicine. We offer state-of-the-art laboratory facilities and staff supporting validation studies, including electronics development, additive manufacturing, and photometric systems. Moreover, we operate a dedicated computing cluster infrastructure for simulations and testing of methods and algorithms.