Procter & Gamble is seeking a Ph.D. intern in Polymer Informatics to improve their tools for polymer discovery. The role involves developing and integrating polymer QSAR models to address data scarcity and enhance model explainability in polymer research.
Develop tooling to enable transfer learning and build explainable models with robust uncertainty quantification.
Build both project-specific and literature data-based models to support internal polymer discovery initiatives.
Integrate these models into P&G's infrastructure and demonstrate their application in polymer discovery.
Qualification
Required
Ph.D. candidate in Chemistry, Chemical Engineering or Materials Sciences, or a related STEM field with strong experience in polymer informatics modeling.
Proven skills in machine learning, QSAR, and data analysis techniques.
Experience with transfer learning and model explainability tools.
Strong communication skills for compiling technical reports and delivering presentations.
Preferred
Proficiency with open-source informatics tools.
Linux.
Python coding.
GitHub.
MLOps.
Benefits
Salary + bonus (if applicable) + benefits
P&G was founded more than 185 years ago as a soap and candle company.