Implicit Human-Computer Interaction with Personalized Psychophysiological AI Models
Work description
Participation in a European project (AI4REALNET) that aims to integrate human contextual information into the interaction between an operator and the system that provides AI-based suggestions. The work will consist in the improvement and evolution of previously developed models, as well as interacting with project partners to integrate algorithms and conduct field studies. Subsequent data analysis, as well as writing articles and possible participation in conferences, will also be part of the activities.
Academic Qualifications
Master's degree in biomedical engineering, bioengineering, electrical and computer engineering, computer engineering, or other similar fields.
Minimum profile required
Advanced knowledge of machine learning models and Python tools for signal processing and machine learning. General knowledge of system architecture and APIs. Previous knowledge of physiological signal processing.
Preference factors
Prior knowledge of psychophysiological variables. Previous work with ECG signals and field data collection using wearable devices.
Application Period
Since 04 Sep 2025 to 08 Oct 2025
Centre
Biomedical Engineering Research