This internship involves supporting computational modeling and molecular dynamics simulations of electrolyte systems relevant to next-generation batteries, with opportunities to contribute to workflow automation, data analysis, and materials discovery in a collaborative, AI-driven environment.
Key Responsibilities
Support computational modeling and simulation of advanced electrolyte systems
Perform molecular dynamics simulations for liquid-phase systems, including system construction and parameter setup
Execute and monitor MD workflows using HPC resources, troubleshooting as needed
Analyze simulation results to determine structural, dynamic, and thermodynamic properties
Develop and improve automated data-processing pipelines for simulations
Convert simulation outputs into reports, visualizations, and presentations
Collaborate with teams to enhance workflow robustness and reproducibility
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
Professional English proficiency is required; candidates must speak English fluently and be able to conduct professional work in English, including technical discussions, documentation, and presentations
Benefits & Perks
Work on real, high-impact problems in next-generation battery materials discovery
Contribute to production-relevant simulation workflows rather than isolated academic projects
Gain exposure to the intersection of molecular simulation, automation, AI for Science, and materials innovation
Collaborate with a global team across simulation, machine learning, and experimental validation