AI-driven Optical Metasurfaces design to Build the Next Generation Fluorescence Microscopes

Artificial Intelligence (AI) has demonstrated remarkable potential in accelerating drug development, provided that sufficient data is available to train robust models. However, acquiring large-scale molecular and cellular response data for both existing and novel drugs remains a bottleneck. Traditional fluorescence microscopes are limited by their low throughput, making data collection impractically slow and resource-intensive.

To overcome this challenge, a new concept in fluorescence microscopy is needed, one that combines high-throughput with cost efficiency. This is where optical metasurfaces come into play. These nanopatterned thin films can replace conventional lenses, enabling optical functionalities that are otherwise unattainable. By leveraging CMOS foundry equipment, imec aims to drastically reduce the production cost of these metasurfaces.

The design of this next-generation fluorescence microscope will be guided by AI, which will address the problem holistically, from optical design to data reconstruction. This doctoral research will focus on the core optical components of the system. You will explore how AI can be used to accelerate the design of optical metasurfaces, ensuring they meet the stringent performance requirements of high-throughput microscopy and integrate seamlessly with reconstruction algorithms.

As a PhD candidate, you will define the foundational technology platform that enables scalable, cost-effective microscopy solutions. While the immediate impact will be in medical and pharmacological applications, the platform may also contribute to solving key challenges in emerging fields such as optical quantum computing.