Physics-Informed Machine Learning Intern

Apply your skills in physics-informed machine learning as a Research Intern at Autodesk in Toronto for Fall 2026. Contribute to innovative projects that merge machine learning with computational simulations.

This internship at Autodesk involves conducting research to integrate machine learning with CFD tools for energy analysis and ventilation optimization. You will develop prototypes, test novel algorithms, and document findings for academic publications or internal reports. The ideal candidate is passionate about engineering and machine learning and possesses a strong foundation in Python and simulation methods.

Key Responsibilities:

• Conduct research on natural ventilation energy analysis tools

• Develop prototypes using physics-informed machine learning

• Test and demonstrate methods in computational simulations

• Write documentation for research findings and prototypes

• Share expertise by conducting learning sessions within the group

Requirements:

• Pursuing a PhD in Engineering, Physics, or similar

• Proficient in Python and AI frameworks like Py Torch

• Experience with physics simulation tools

• Knowledge of numerical solvers and data-driven methods

• Published research experience in top-tier venues

Leverage your research and programming expertise to make a meaningful impact at Autodesk.
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