About the project
This PhD project invites you to transform specialty fibre fabrication through the application of machine learning.
Specialty optical fibres are foundational to breakthroughs in fields spanning high-power lasers, advanced manufacturing, high-speed telecommunications, healthcare, and quantum technology. Each of these domains demands fibres with unique properties, such as power handling for industrial lasers, stability for quantum applications, or precision for healthcare diagnostics.
However, optimising fibre characteristics through existing fabrication processes is complex and resource-intensive, especially as even the smallest variations in fabrication parameters can dramatically impact fibre performance.
By leveraging the predictive power of machine learning, you will be developing methods to model and fine-tune the intricate process variables, from dopant levels to temperature profiles and drawing conditions, enabling the production of fibres tailored to exact specifications. Imagine AI-driven insights that uncover brand new fabrication recipes and unlock the capability for real-time fabrication adjustments to create fibres optimised for each unique application.
You will apply machine learning techniques to understand how fibre fabrication steps, using methods such as Modified Chemical Vapor Deposition (MCVD), affect the final properties of fibres doped with rare-earth elements like Erbium, Ytterbium, and Thulium.
Your objective will be to achieve superior optical properties, unmatched reliability, and exceptional yield, and ultimately unleash the production of fibres that push the limits of performance in lasers, improve transmission quality in telecoms, enhance imaging in healthcare, and meet the demanding requirements of quantum technologies.
Your research will redefine fibre fabrication, setting the stage for the next generation of specialty optical fibres.
