AI in Circular Economy Research Benchmarking
Data Science
Innovation
Develop cutting-edge methodologies to identify, curate, and validate best practices in circular economy research using advanced data analytics
Teaching
Overview
This thesis offers a unique opportunity to work at the intersection of sustainability, artificial intelligence, and data science. You’ll develop cutting-edge methodologies to identify, curate, and validate best practices in circular economy research using advanced data analytics techniques.
Key Focus Areas
- Data-driven best-practice identification using machine learning algorithms
- Best-practice curation through automated content analysis
- Validation of best-practice recommendations via empirical testing
- Community-of-best-practice exchange platform development
Ideal For
Students with a background in data science, computer science, business informatics, or environmental studies with strong analytical skills and interest in sustainability.