AI in Circular Economy Research Benchmarking

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.