Research Intern, Physics-Informed Machine Learning
AMER - Canada - Ontario - Toronto - University Ave
CAD 72K-105K (estimate) Entry-level Full Time Internship
Tasks
- Conduct original physics informed machine learning research
- Develop and apply novel physics informed machine learning techniques
- Develop prototypes for air flow and heat transfer analysis
- Implement prototype code to test methods
- Integrate open source and in house libraries
- Parameterize tools using CFD simulations
- Present learning sessions for the SOS Group
- Research energy analysis tools for natural ventilation
- Write research documentation for publications and white papers
Perks/Benefits
- Flexible workplace hybrid remote options
- Mentorship
- Paid internship
- Professional development
- Tech talks
Skills/Tech-stack
Airflow Simulation | CFD | Computational tools | Data-driven | Data-driven simulation | Flax | Heat Transfer Simulation | Heat transfer | Machine Learning | Natural ventilation | Numerical solvers | Physics-informed machine learning | PyTorch | Python | TensorFlow
Education
Roles
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