Project: Machine Learning for Enhanced Silicon Photonics Devices
We are seeking a postdoctoral researcher with interest and experience in integrated photonics to join the Silicon Photonics team at the Center for Nanoscience and Nanotechnology (C2N). The project stems from a longl asting collaboration with the National Research Council Canada (NRC) and aims at developing accurate silicon photonics surrogate models using machine learning. In particular, we will address the key open challenge of modeling the impact of fabrication and operation environment on the perfromance of photonic devices. We will exploit both simulations and optical measurements in a data-efficient manner, and leverage transfer learning and active learning methods. The developed models will then be used to anticipate and pre-emptively compensate for fabrication errors, providing an innovative approach to design and calibrate large photonic circuits
The full job description can be found here.