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Research Engineer

Research Engineer

QpiVolta TechnologiesBengaluru, Karnataka, India
6 days ago
Job description

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