Research and development of new algorithms for processing and classifying physiological signals.
[Open soon]
Work description
Processing of physiological signals (pre-processing, filtering, feature extraction in the time, frequency, and time-frequency domains). Development and validation of machine learning and deep learning models; integration and analysis of data from wearable and clinical monitoring devices and clinical databases. Experimental evaluation of algorithms, development, and deployment. Support in data collection and documentation of the work performed.
Academic Qualifications
Bachelor’s degree in biomedical engineering, Electrical Engineering, Computer Science, or a similar field.
Minimum profile required
Experience in biomedical signal processing.Knowledge of machine learning/deep learning.Experience in scientific programming (e.g., Python and/or MATLAB) and code management tools.Good knowledge of written and spoken scientific English.
Preference factors
Previous work in developing algorithms for biomedical signal processing and machine learning/deep learning techniques with physiological signals, namely ECG. Previous knowledge in collecting physiological data and managing and preparing it for analysis. Prior experience in a hospital setting in the field of biomedical engineering. Willingness to pursue a master's thesis within the research group.
Application Period
Since 12 Feb 2026 to 25 Feb 2026
[Open soon]
Centre
Biomedical Engineering Research