SES AI is seeking a Computational Chemistry Interns to join the Molecular Universe team and support computational modeling and simulation of advanced electrolyte systems.
Requirements
- PhD (or PhD candidate) in Computational Chemistry, Materials Science, Chemical Engineering, Physical Chemistry, or a related field
- Hands-on experience with molecular dynamics simulations, particularly for liquid-phase systems
- Familiarity with common simulation tools such as GROMACS, LAMMPS, OPENMM, or similar packages
- Experience with electrolyte systems, ionic systems, battery-related simulations, or sodium-ion systems is strongly preferred
- Understanding of molecular force fields, including basic principles of force field development and parameterization; direct experience is preferred
- Programming skills in Python or similar languages for data analysis, workflow automation, and simulation pipeline development
- Strong problem-solving skills and the ability to diagnose simulation instability, convergence issues, and physical inconsistencies
- Excellent communication skills, with the ability to clearly present technical findings to both technical and non-technical audiences
- Ability to work effectively in a collaborative, international research environment
Benefits
- Opportunity to work on real, high-impact problems in next-generation battery materials discovery
- Contribution to production-relevant simulation workflows rather than isolated academic projects
- Exposure to the intersection of molecular simulation, automation, AI for Science, and materials innovation