PhD Position in Biomedical Signal Processing and Machine Learning for Wearable Physiological Monitoring Empa in Switzerland

Empa, a leading research institution within the ETH Domain in Switzerland, is offering a PhD position in Biomedical Signal Processing and Machine Learning for Wearable Physiological Monitoring. The position is based at the Biomimetic Membranes and Textiles laboratory, where interdisciplinary teams develop, integrate, and validate novel sensing systems, particularly for textile applications. The research focuses on creating new sensor concepts, experimental characterisation, and systematic validation under realistic conditions. This includes setting up measurement systems, signal processing and analysis, and assessing measurement accuracy, robustness, and long-term stability.

The successful candidate will develop data processing pipelines for multimodal physiological signals, including pre-processing, feature extraction, and data fusion from wearable sensing systems. You will design and validate machine learning models for predictive monitoring of physiological states, analyse large experimental datasets, and quantify sensor performance under varying physiological and environmental conditions. Statistical evaluation and model validation using controlled measurements and sensing-dummy reference data are integral parts of the project. Collaboration with project partners and dissemination of results through reports, visualisations, and scientific publications are expected.

Applicants should hold an M.Sc. in Data Science, Computer Science, Engineering, Physics, Statistics, or a related field, and be motivated to apply advanced analytics to real-world digital health challenges. Strong foundations in signal processing and proficiency in Python or MATLAB are required. Experience with biomedical signals or signal quality assessment is advantageous, as is initial experience in machine learning and statistical modelling. Curiosity, willingness to learn, and familiarity with physiological data (e.g., heart rate variability) are a plus. The ideal candidate enjoys working with complex, multimodal datasets and developing robust algorithms for continuous monitoring and predictive modelling. Comfort with coding, data analysis, and experimental validation in lab and field settings is essential. Independent work, analytical thinking, initiative, and excellent English skills are required; German is a plus.

Empa offers an application-oriented research environment, close collaboration with interdisciplinary teams and national and international partners, and active support for professional and personal development. The position is fully funded for three years, with salary and benefits according to Empa and ETH Zurich standards. The doctoral project will be carried out in close collaboration with the Department D-HEST at ETH Zurich, and the doctoral degree will be awarded by ETH Zurich. Empa values inclusion and respect, welcoming all individuals interested in innovative, sustainable, and meaningful activities.

To apply, submit your complete online application, including a letter of motivation, CV, certificates, diplomas, and contact details of two reference persons, exclusively via the Empa job portal. Applications by e-mail or post will not be considered. For more information and to access the application portal, use the provided link.