PhD Scholarship in Structural Condition Monitoring of Large Civil Structures

Project Description

Structural safety is an essential issue for all civil structures such as bridges and buildings. In many developed countries, the budget for the maintenance of structures is costly and has been annually expended. Despite these efforts, damage in these structures seems to be inevitable since they are subjected to various extreme loadings and environmental impacts, which might have been underestimated in the design process. It is, therefore, important to detect, locate and estimate damage in structures so that their service lives can be prolonged by taking appropriate actions.

The successful candidate will work with Dr. Khac Duy (Ronan) Nguyen on an Australian Research Council (ARC) project “Innovative soft-computing for condition assessment of large infrastructure”. The project explores new methodology to examine structural health condition based on vibration measurement, signal processing and data analysis, evolutionary computation, and artificial neural networks. 

School of Civil and Environmental Engineering, Queensland University of Technology

Queensland University of Technology (QUT) is a research-intensive university, and constantly strives to improve its position within Australia and the world university rankings. QUT’s success in high-impact research has been acknowledged through globally recognised awards and rankings. Research in Structural Engineering has grown considerably in recent years with about 40 PhD students, 9 research assistants/fellows and 10 academics. Many projects have been in the area of structural health monitoring (SHM), which is a research priority at QUT. They are supported by high-performance computing facility, which is essential for projects requiring extensive modelling and data analysis. The School of Civil and Environmental Engineering has an off-site modern structural lab, where large-scale structural testing is available. The school is also well equipped with SHM facilities such as universal data acquisition, high-sensitivity accelerometers, laser-based displacement sensors. In addition, as a lead node for the Australian Data Science Network, QUT Centre for Data Science (QUT-CDS) provides excellent environment and expertise for the studies in applied data science and soft computing. 

Eligibility Criteria

You must:

•Meet the academic and English language entry requirements for QUT’s Doctor of Philosophy (PhD). More details can be found here: https://www.qut.edu.au/courses/doctor-of-philosophy and https://www.qut.edu.au/research/study-with-us/how-to-apply

•Have recently completed one of:

        oa Master degree by research with technical publications in civil engineering, structural engineering, or related fields. 

        oan Australian Bachelor first-class honours (H1) degree or equivalent in civil engineering, structural engineering, or related fields.

We’d also prefer you to have:

•Research experience in structural dynamics, structural health monitoring, evolutionary computation, or machine learning. 

•Computer modelling skills. 

•Scientific writing skills for publications.

What you’ll receive

•The successful applicant (both domestic and international) will receive a living allowance of $28,597 per annum for three years, indexed annually, with a potential of six-month extension (subject to approval by QUT).

•A successful international student will also be considered for a research degree tuition fee sponsorship. 

Application

Interested applicants are invited to contact Dr. Khac Duy (Ronan) Nguyen at [email protected] with a cover letter outlining your interest and suitability for the position, a detailed CV with contact details of two referees, English testing scores (for international applicants), degree certificates, and other documents you wish to be considered (academic transcripts, letters of recommendation, etc.). You are also welcome to contact Dr Khac Duy (Ronan) Nguyen for further information. 

Application Closing Date: 11 April 2022 or until a successful candidate is identified. We are seeking to commence this project as soon as possible with expected commencement date as July 2022.