Research Intern: Physics-Informed ML

Position: Autodesk Research Intern: Physics-Informed ML
Join Autodesk's Toronto office as a Research Intern focused on physics-informed machine learning for Fall 2026. Develop prototypes to enhance airflow and heat transfer analysis in buildings.

The SOS Group at Autodesk Research is looking for an enthusiastic PhD candidate to conduct research from September to December 2026. Applicants must have a solid foundation in data-driven simulation methods and experience with Python, AI training, and simulation tools. This opportunity emphasizes original research and prototype development in energy analysis.

Key Responsibilities:

• Research energy analysis tools using CFD simulations

• Apply innovative physics-informed machine learning techniques

• Develop and implement prototypes for testing concepts

• Write detailed documentation for publications or internal reports

• Facilitate technical learning sessions within the group

Requirements:

• PhD student with a graduation date after January 2027

• Hands-on experience with numerical solvers and physics tools

• Proficiency in Python and AI frameworks like Py Torch

• Experience in publishing research in leading conferences

• Knowledge of data-driven simulation practices

Contribute to significant advancements in research at Autodesk while refining your expertise.
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