- Study of art stay on health recognition and well-being with machine learning techniques - Analysis of use cases and definition of specific goals and requirements (for example, what data should be used) - Collect data and perform preprocessing (e.g. remove noise, damaged data, ...) - Describe/study data from infrastructure (e.g. wearable data and sensors) - Create Machine Learning models for Human Activity Recognition using Pocket Data Mining methods. - Test and validate the models in laboratory and business environment.
Master's degree in Computer Science, Electrical, Informatic or similar
Minimum profile required
- Final graduation mark higher or equal to 14.- Fluency in English (spoken and written)
- Enrollment in a doctoral program in Computer Science, Electrical, Informatic or similar; - Experience in participating in research projects; - Experience in Machine Learning, Data Mining
Since 20 Oct 2021 to 03 Nov 2021
Cluster / Centre
Computer Science / Artificial Intelligence and Decision Support