Job Overview
* Two-year fixed-term, full-time contract, based at Bentley Campus.
* Ranked in the top 1% of universities worldwide (ARWU 2025).
* Diverse and dynamic team fostering innovation, collaboration and sustainability.
Project
The project aims to develop advanced deep learning methods for automated bridge inspection, condition assessment, and long-term structural performance prediction. Working at the intersection of civil engineering, deep learning, and infrastructure asset management, you will contribute to research that has a direct impact on real-world civil infrastructures.
Role
You will lead research on developing advanced deep learning models for structural health monitoring, with a focus on bridge inspection and monitoring systems.
Responsibilities
* Conduct high-quality research in physics-informed neural networks and deep learning for structural health monitoring.
* Analyze and interpret experimental data and prepare regular progress reports.
* Develop and evaluate models for bridge inspection, damage detection and long-term performance prediction.
* Contribute to research publications in leading journals and present findings at national and international conferences.
* Supervise HDR students and research assistants.
* Participate in team discussions, brainstorming sessions and project planning meetings.
Selection Criteria
* PhD in Civil or Structural Engineering (or near completion).
* Demonstrated research experience in deep learning and computer vision for structural health monitoring.
* Potential to secure external competitive research funding.
* Emerging publication record appropriate to career stage.
* Ability to work collaboratively with industry partners and multidisciplinary teams.
* Excellent written and verbal communication skills.
Desirable
* Knowledge of structural vibration testing, long-term monitoring data processing and condition assessment research.
Requirements
* Work rights matching the tenure of the role. Applications accepted from Australian citizens, permanent residents and temporary visa holders.
* Successful applicants will be subject to a national police clearance, background, integrity and reference checks.
Benefits
* 17% superannuation and various salary packaging options.
* Paid parental leave (26 weeks for primary caregiver, 3 weeks for non-primary), personal leave (14 days) and annual leave (20 days).
* 12 public holidays each year and additional university days over Christmas/New Year.
* Breastfeeding facilities and campus-based childcare.
* Flexible work arrangements including return-to-work provisions.
* On-campus medical centre.
* Academic carer support scheme and other inclusion initiatives.
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