To live longer, healthier and more active, people at any age has to follow simple and clear
suggestions that cover all the 4 pillars of health: physical activity, nutrition, mindfulness, and
sleeping. Unfortunately, due to the intrinsic (e.g., daily-life habits) and extrinsic (e.g.,
environmental change) factors, people are far to have a healthy life and, thus, there is an
increase of chronic diseases, mental disorders, and premature death. In the literature, several
behavioural change theories have been defined and studied to help people to make a change in
In this Ph.D. thesis, we will investigate how to design, implement, and validate a holistic recommender system inspired by behavioural change theories and taking into account the 4 pillars of health all together.
The recommender system will be designed with AI and ML capabilities able to personalize the experience to the kind of user considering working and daily-life habits, age, gender, health status, and preferences.
The candidates are requested to:
- Have finished a degree in computer science. A double degree with Mathemathics will be highly valued.
- Be eager to learn new mathematical models and technologies, specifically in the Big Data/Machine Learning area.
- Have a good knowledge of Python.
- Be able to work with development tools such as Git.
- Be a proficient developer.
- Have excellent marks.
- Be a heavy worker and motivated by challenges.