About the project
This PhD project aims to develop machine learning algorithms for the inverse design of metasurfaces, targeting applications in intelligent sensing for complex environments, such as biomedical fields and consumer electronics.
Optical metasurfaces are planar nanostructures with unique electromagnetic properties that hold transformative potential in next-generation optical sensing. This PhD project, supervised by Dr Xu Fang from the University of Southampton’s School of Electronics and Computer Science, will focus on designing these devices, particularly those with complex geometries and materials for advanced sensing applications.
Your research will focus on developing cutting-edge machine learning algorithms for the inverse design of metasurfaces, an area poised to revolutionise sensing technologies in complex environments. By exploring deep learning techniques, you will design metasurfaces with extraordinary electromagnetic capabilities, using the University’s state-of-the-art supercomputing clusters. In collaboration with a team of students, technicians, and academics, your designs will undergo experimental validation to drive real-world advancements. You will also contribute to an ongoing research partnership with MIT in this research area, joining our long-term collaborative efforts.
Depending on project progress and funding, you may have the chance to work in collaborators’ labs in Japan and US for up to three months. Your will also have chances to collaborate with academics in the School who are currently commercialising artificial intelligence-based technologies for electronics applications.
We seek a highly motivated candidate with a background in machine learning, photonics, or electronics. Proficiency in Python or MATLAB is highly desirable. For more information, please contact Dr Xu Fang at x.fang@soton.ac.uk.
