Computer Science
[Closed]
Work description
- examine the access logs from platforms providing behavioral digital therapies to identify patterns in user behavior; - develop metrics to quantify user engagement, such as session frequency, duration, and interaction types. - analyze the relationship between these metrics and other engagement metrics using statistical techniques; - analyze the relationship between metrics and therapy outcomes using statistical and machine learning techniques. - build predictive models to identify key user behaviors that correlate with successful therapy outcomes. - validate the models using appropriate techniques, such as cross-validation and testing on unseen data. - develop recommendations to enhance user engagement and therapy effectiveness based on the findings. - write and publish a scientific article.
Academic Qualifications
Degree in informatics and computing engineering or related field
Minimum profile required
- ability to read, write and speak in English.
Preference factors
- knowledge of machine learning.
Application Period
Since 14 Nov 2024 to 04 Dec 2024
[Closed]
Centre
Human-Centered Computing and Information Science