QpiVolta Technologies
Website:
qpivolta.tech
Job details:
Research Engineer - Battery Modeling
Position Overview
QpiVolta Technologies is seeking a Research Engineer to work on accelerating battery modeling
through advanced Machine Learning techniques. The ideal candidate will have a strong background in both computational chemistry and machine learning, with experience in
multi-scale modeling of materials and interfaces.
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.
Required Qualifications
● Master’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)
○ Battery design software tools
Technical Skills
● 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)
Battery Modeling Workflow Experience
● 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
● Understanding of different modeling scales:
○ Atomistic simulations for interface phenomena
○ Mesoscale modeling for particle interactions
○ Cell-level performance prediction
○ Pack-level thermal and electrical behavior
Preferred Qualifications
● 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
Required Competencies
● Strong analytical and problem-solving skills
● Excellent programming and data analysis capabilities
● Ability to work independently and as part of a team
● Strong written and verbal communication skills
● Strong programming skills preferably in Python
● Experience with scientific documentation and technical writing
Project Focus Areas
● 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
Click on Apply to know more.