Ptychographic Microscope for Advanced Metrology and Inspection

Ptychographic imaging offers useful insights into both non-carbon material properties and biological label-free processes. However, current microscope systems are often expensive, bulky, and have limitation on accuracy, speed and adaptability across use cases. This project aims to develop a compact, scalable and cost-effective microscope system based on coherent diffractive imaging technique using advances optics and imaging techniques suitable for diverse applications, where conventional microscope face challenges such as label requirement, short working distance and limited Field of view and resolution, restricting their ability for label-free, high-accurate inspection. By integrating Ptychographic method with advanced optics and illuminations, this project will overcome these limitations and enable superior imaging methodology.

The work will focus on optical components enhancement, custom spectral filters designs, and optimized illumination settings. The candidate will take responsibility on design, fabrication, and characterization of key elements of the system, with an emphasis on precision metrology to ensure reliability and reproducibility. The system should include a well-designed, extensible interface to support additional common sensor types, as needed by users.

The project includes building embedded processing pipelines that reduce raw data at the sensor level. The candidate will develop AI and machine learning algorithms for anomaly detection, pattern recognition and efficient data compression. To ensure practical usability, these models will also be optimized to run efficiently on edge hardware, with support for cloud-based data storage and remote access when needed.

Real-world test cases will include semiconductor metrology for deep 3D trench inspection, biomedical breast cancer classification in pathology, and aquaculture water monitoring for microorganism detection. These scenarios provide practical environments to validate the system’s performance. The similar architecture can be adapted for use in multiple sectors of environmental monitoring, food safety, and industrial inspection.

The PhD will be comfortable working at across the imaging system including optical design, simulation, embedded computing, and applied AI. The ideal candidate should be comfortable working at the intersection of hardware and software in different sectors, and be interested in developing sensing systems that are accurate, efficient, and usable outside the lab.