About this Position
This internship position will help build a system that blends machine learning (ML), physicsbased modeling and packaging science to predict packaging behavior during compatibility tests. This role is perfect for students excited about the intersection of data science, engineering and realworld product performance.
What youll do
- Collect, organize and sort historical packaging test data from multiple sources
- Analyze and structure results
- Develop and evaluate ML models - Random Forest, XGBoost, to predict storage test outcomes
- Contribute to hybrid AI models by integrating physicsbased equations with ML techniques
