PhD Position in Machine Learning for Wearable Physiological Sensing Systems at Empa/ETH Zurich Empa in Switzerland

Empa, a leading research institution within the ETH Domain, is offering a fully funded PhD position in the field of machine learning for wearable physiological sensing systems. The opportunity is based at the Biomimetic Membranes and Textiles laboratory, where interdisciplinary teams focus on developing, integrating, and validating novel sensing systems, particularly for textile applications. The research aims to advance digital health solutions by enabling continuous, long-term monitoring of individuals using innovative sensor technologies.

The doctoral project centers on the development of 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, analyze large experimental datasets, and quantify sensor performance under varying physiological and environmental conditions. Statistical evaluation and model validation will be conducted using controlled measurements and reference data from sensing dummies. Collaboration with project partners and dissemination of results through reports, visualizations, and scientific publications are integral parts of the role.

Applicants should hold an M.Sc. in Data Science, Computer Science, Engineering, Physics, Statistics, or a related field. Strong foundations in signal processing and proficiency in Python or MATLAB are essential. Experience with biomedical signals or signal quality assessment is advantageous, as is familiarity with machine learning frameworks such as scikit-learn, XGBoost, or PyTorch, and statistical modeling techniques like mixed models, ANOVA, and power analysis. Curiosity, willingness to learn, and familiarity with physiological data (e.g., heart rate variability) are beneficial. The ideal candidate enjoys working with complex, multimodal datasets and developing robust algorithms for continuous monitoring and predictive modeling, combining coding, data analysis, and experimental validation in both lab and field settings. Independent work, analytical thinking, and initiative are important, and excellent English skills are required; German is a plus.

Empa offers an application-oriented research environment, close collaboration with the Department D-HEST at ETH Zurich, and a strong professional network with national and international partners. The position is initially limited to three years, with the doctoral degree awarded by ETH Zurich. Empa actively supports professional and personal development, fostering a culture of inclusion and respect. The start date will be mutually agreed upon.

To apply, submit your application online via the provided link. Prepare your CV, cover letter, and relevant documents. For further information, contact Empa HR. This is an excellent opportunity to contribute to cutting-edge research in digital health and wearable sensing technologies, and to build a strong foundation for a future career in academia or industry.