This PhD opportunity at University College Cork (UCC), in collaboration with CERN, focuses on the development of Large Language Models and AI for ground-tunnel interaction and infrastructure maintenance. The project aims to address the challenge of performance degradation in large-scale underground infrastructure, such as tunnels and pipelines, by integrating diverse data sources including crack images, ground-penetrating radar (GPR) images, continuous strain sensor data, and historical borehole logs. The research will develop a systematic framework to correlate these data sources with the condition of concrete linings, providing insights into the long-term behavior of underground structures under varying hydrogeological conditions.

The supervision team includes Dr. Zili Li from UCC and collaborators at CERN, offering a unique interdisciplinary environment at the intersection of civil engineering, computer science, and artificial intelligence. The ideal candidate will have a strong background in civil engineering or computer science, with experience in structural health monitoring and machine learning considered advantageous. Applicants must hold at least a 2.1 honours Bachelor's degree or equivalent and demonstrate English language proficiency if required.

Currently, a 50% PhD scholarship is available, with the possibility of additional funding based on academic progress. The application process requires submission of a CV (maximum 2 pages) and a cover letter detailing relevant experience and motivation. This project is ideal for candidates interested in AI applications in infrastructure, data integration, and the future of underground construction and maintenance. For more information, refer to the relevant publication: Image-based large language model approach to road pavement monitoring.