US Computational Chemistry Intern Materials Modeling Molecular Simulation
SESRemote
Internship
Posted March 19, 2026
Energy Storage
Remote
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Application opens on company website
Job Description
This role involves supporting computational modeling and molecular dynamics simulations of electrolyte systems relevant to next-generation batteries, with responsibilities including workflow execution, data analysis, and collaboration within a global team focused on AI-driven materials discovery.
Key Responsibilities
- Support computational chemistry modeling and simulation of advanced electrolyte systems
- Perform molecular dynamics simulations for liquid-phase systems, including system setup and parameter configuration
- Execute the full MD workflow, including job submission, resource management, and troubleshooting
- Analyze simulation results to determine structural, dynamic, and thermodynamic properties
- Develop and improve automated data-processing pipelines for simulation efficiency and reproducibility
- Create reports, visualizations, and presentations based on simulation outputs
- Collaborate with internal teams to enhance workflow robustness and scalability
- Contribute to force field development, optimization, and validation for electrolyte systems
- Explore higher-accuracy or higher-efficiency simulation methodologies
- Participate in the engineering and automation of simulation workflows
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, including technical discussions, documentation, and presentations
- Candidate must be based in the U.S. West Coast region to support business operations
- Duration of the internship is 6 months
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
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