[US] Computational Chemistry Intern (Materials Modeling/Molecular Simulation)

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

Contribute to force field development, optimization, and validation for electrolyte or ion-containing systems

Contribute to the SES Molecular Universe project by supporting computational chemistry modeling and simulation of advanced electrolyte systems

Independently or collaboratively perform molecular dynamics simulations for liquid-phase systems, especially electrolytes, including system construction, initial structure generation, and simulation parameter setup

Execute the full MD workflow, including job submission, HPC resource utilization, run monitoring, troubleshooting, and issue resolution

Analyze simulation results in depth, including but not limited to:

Structural properties such as radial distribution functions (RDF), coordination numbers, and solvation structures

Dynamic properties such as diffusion coefficients and ion transport behavior

SES AI is a leader in AI-driven materials discovery, building the

Molecular Universe (MU)

platform to accelerate the development of next-generation battery chemistries. Our work integrates physics-based simulations, machine learning, and large-scale data infrastructure to enable rapid innovation in material science with a dedication to AI for Science.

To learn more about SES, please visit:

www.ses.ai