Battery Modeling Engineer
24 hours ago
We are seeking a highly skilled Battery Modeling Engineer to accelerate our battery modeling initiatives through advanced Machine Learning techniques at QpiVolta Technologies.
Key Responsibilities:- Develop and implement machine learning models for battery material interface and transport phenomena.
- Integrate multi-scale modeling approaches spanning quantum chemistry, molecular dynamics, and continuum models.
- Apply and fine-tune ML force fields for accurate materials simulation.
- Contribute to the development of battery design and optimization workflows.
- Collaborate with interdisciplinary teams on battery modeling projects.
- Bachelor's degree in Chemistry, Materials Science, Chemical Engineering, Mathematics, Physics, or a related field.
- Experience applying Large Language Models in Scientific Domains.
- Strong background in computational modeling at multiple scales: Density Functional Theory (DFT), Molecular Dynamics (MD), Coarse-grained modeling, Continuum modeling.
- Experience with relevant software tools: LAMMPS for molecular dynamics simulations, DFT software packages (e.g., VASP, Quantum ESPRESSO, or similar), PyBaMM, Battery Design Studio (Python Battery Mathematical Modelling).
- Demonstrated experience in machine learning model development and implementation.
- Force field development and fine-tuning.
- Integration of multi-scale modeling approaches.
- Python programming and scientific computing libraries.
- Version control systems (e.g., Git).
- Proficiency in electrochemical modeling workflows: P2D (pseudo-two-dimensional) models for cell-level simulation, SPM (single particle model) for simplified cell analysis, Newman model implementation and modification, Electrode-scale transport phenomena modeling.
- Familiarity with multi-physics coupling approaches: Thermal-electrochemical coupling, Mechanical-electrochemical coupling, Aging mechanisms integration.
- Experience with automated workflow tools: Battery parameter estimation pipelines, Materials screening workflows, Automated DFT calculation setup, High-throughput simulation management.
- Previous research experience in battery materials or electrochemistry.
- Publications or contributions to papers/open source in relevant fields.
- Experience with high-performance computing environments.
- Knowledge of electrochemical characterization techniques.
$120,000 - $180,000 per year, depending on experience.
Benefits:- Comprehensive health insurance.
- Retirement plan matching.
- Generous paid time off.
- Ongoing education and training opportunities.
- Battery material interface modeling.
- Transport phenomena simulation.
- Stability analysis across multiple scales.
- ML-accelerated materials discovery.
- Integration of quantum, molecular, and continuum approaches.
- Workflow optimization and automation.
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