Leuven | More than two weeks ago
Using machine learning and other advanced algorithms to design high-performance on-chip fiber couplers on imec silicon photonics platform, targeting low loss, wide optical bandwidth and enabling polarization management
Silicon Photonics (SiPho) is a fast-growing technology addressing many applications such as data and quantum communication but also sensing and imaging (LiDAR). Especially for communication applications, silicon photonics is playing a key role to have lower power consumption and higher speed at the same time with lower cost than traditional compound semiconductor photonics. As an importance of silicon photonics optical I/O increases, industry major players such as intel, Nvidia, TSMC, Samsung are also shipping the silicon photonics products or trying to have faster and energy-efficient products. As a world-renowned research center in this field, imec has in-house 200mm and 300mm CMOS pilot lines to process cutting-edge optical devices at wafer scale, including high-performance devices for light modulation, switching, coupling, filtering, and detection at data rates of 50GB/s and beyond.
This PhD research focus on developing high-performance fiber-chip interface to address the industry needs for next-generation products where more then ever every loss needs to be eliminated. Current fiber grating couplers are limited by its high loss, limited bandwidth, and polarization sensitivity. For high-channel-count or course wavelength-division-multiplexing optical circuits, it is crucial to increase the fiber interface optical bandwidth to facilitate wafer-level testing. For photonic receivers, a polarization-splitting fiber interface would reduce the difficulty for packaging. For many emerging applications including quantum photonics, it would also be desirable to have extremely loss low fiber couplers. To achieve these novel design concepts, it would be crucial to adopt advanced algorithms including machine learning. The PhD student is expected to carry out independent and novel research in the silicon photonics device platform team, during which he/she will master Python programming for scientific data processing, and the modelling, simulation, and characterization of silicon photonics devices and circuits.
In this research, the PhD student will carry out:
Required background: Master’s degree in EE or Physics, Nanoscience and Nanotechnology Preferred: experience with Python programming, and integrated photonics design/simulation/characterization
Type of work: 40% modeling/simulation, 40% experimental, 20% literature
Supervisor: Yanlu Li
Daily advisor: Lirong Cheng
The reference code for this position is 2025-156. Mention this reference code on your application form.