The business problem involves investigating the decomposition of polymers using zeolite catalysts through advanced computational methods to understand reaction mechanisms, catalyst activity, and optimize catalytic pathways.
Requirements
- Demonstrated expertise in atomic-scale simulations (e.g., MD, DFT, ML-FF)
- Demonstrated proficiency in computational programming (Python, C++, or related programs)
- Ph.D. in Materials Science, Physics, Chemistry, Mechanical Engineering, or a related field
Responsibilities
- Performing DFT simulations to study key reaction steps in polymer cracking and dehydrogenation.
- Developing and applying machine learning force fields for large-scale reactive simulations.
- Integrating ML methods to accelerate exploration of catalyst–polymer interactions and optimize catalytic pathways.
- Collaborating with experimental and computational partners to validate predictions and refine models.
- Investigating reaction mechanisms, catalyst activity, kinetics, and structure–function relationships using a combination of density functional theory (DFT), machine learning force fields (ML-FF), and data-driven machine learning models.
Other
- Ph.D. in Materials Science, Physics, Chemistry, Mechanical Engineering, or a related field
- Demonstrated experience with writing research publications
