Research Intern, Physics-informed Machine Learning

Autodesk Autodesk · Enterprise · Toronto, ON +1

Research intern at Autodesk Research focusing on combining machine learning with computational tools for analyzing air flow and heat transfer in building environments, specifically through physics-informed machine learning and CFD simulations.

What you'd actually do

  1. Research on energy analysis tools for natural ventilation and their parameterization using CFD simulations.
  2. Conduct original research in developing or applying novel techniques in physics-informed machine learning.
  3. Implement prototypes to test and demonstrate the ideas and methods
  4. Work with both open-source libraries and in-house libraries to develop the prototypes
  5. Write documentation of the work, either as academic publication or internal white paper

Skills

Required

  • PhD student in Engineering, Physics, Mathematics, Computer Science, or related disciplines
  • Experience with data-driven methods in simulation
  • Experience with development of physics simulation tools and numerical solvers
  • Experience with AI model training and ecosystems (PyTorch, TensorFlow, Flax etc)
  • Excellent knowledge of Python
  • Experience in publishing at top-tier conferences and journals

Nice to have

  • passionate and skilled research intern

What the JD emphasized

  • PhD degree
  • publishing at top-tier conferences and journals

Other signals

  • physics-informed machine learning
  • CFD simulations
  • energy analysis tools
  • Python
  • PyTorch, TensorFlow, Flax