Project description: Many kilometres of underground infrastructure in a large-scale network (e.g., tunnel, pipelines) may heavily encounter performance degradations during long-term service. In the past, the resultant structural condition data, historical borehole logs and relevant hydrogeological reports have been used to evaluate the long-term structure serviceability. However, hydrogeology uncertainty and variation along the tunnel infrastructure present a significant challenge to the understanding of ground-tunnel interaction on a very large city scale. This research postgraduate student project will specifically address the impact of hydrogeology spatiotemporal variation on large-scale tunnel infrastructure over many kilometres using cutting-edge computer vision models and machine learning algorithms. The research outcome aims to give more insights into large-scale tunnel design and maintenance using big data analytics along with geoengineering knowledge than previously available by conventional methods.
Position Description: In this project, the research master will focus on hydrogeological data transformation, and interpretation. The one-year research master (may be extended to a PhD position) will be based at UCC. She/he will undertake this CERN project along with another research master, a Postdoc under the joint supervision of CERN and UCC.
Candidate Experience: The postgraduate student candidate should have a minimum 2.1 in an honours Bachelor’s degree in Civil Engineering / Computer Science, or an equivalent standard from an overseas university. The postgraduate student whose first language is not English must provide evidence of English language proficiency (e.g. IELTS or TOEFL) according to UCC entry requirement. Some experience in structural health monitoring and machine learning would be an advantage.
Application:
- Master / PhD student applicant
Please e-mail a CV (max. 2 pages) and a cover letter outlining your experience and motivation to Dr. Zili Li (zili.li@ucc.ie). Early application is highly encouraged.