Description

You will develop and validate numerical models to solve complex physical systems, including thermal, fluid dynamics, structural, electromagnetic, and battery systems.

This role is on-site.

Responsibilities

• Implement custom numerical solvers and simulation tools using Python and scientific computing libraries.
• Translate theoretical models into scalable, maintainable code for product integration or research.
• Support model calibration and validation using experimental or field data.
• Maintain code versioning via Git and apply software engineering practices like modular design, unit testing, and CI/CD pipelines.
• Integrate empirical data into physical models through data-driven modeling techniques.

Required Skills

• 5 to 10 years of experience in numerical modeling, simulation, or scientific computing.
• Strong command of Python programming.
• Proficiency with NumPy, SciPy, SymPy, and Matplotlib.
• Experience with PyTorch (for PDEs) or FEniCS.
• Experience with data-driven modeling and empirical data integration.
• Dot net programming skills.
• Master’s or Ph.D. in Mechanical Engineering, Applied Mathematics, Physics, or Computational Engineering.
• Strong debugging, problem-solving, and analytical skills.

Preferred Skills

• Basic understanding of Optics and Display Design.

Key Skills

Education

Master’s or Ph.D. in Mechanical Engineering