Research Fellow: AI-Driven Structural Reliability

Nanyang Technological University; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

NTU Singapore, School of Civil and Environmental Engineering, invites applications for a Research Fellow to advance computational reliability methods for structural and infrastructure systems under uncertainty, focusing on high-dimensional probabilistic analysis, surrogate modelling, and AI-enabled techniques.

The role covers developing efficient algorithms, applying methods to case studies, publishing in international journals, and contributing to proposals while supervising students within the

Qualifications

• PhD in Civil Engineering, Structural Engineering, Engineering Mechanics, Applied Mathematics, or a closely related field.
• Strong background in structural reliability, probabilistic modelling, stochastic dynamics, uncertainty quantification, or related areas.
• Experience in developing and implementing computational methods for engineering analysis.
• Proficiency in scientific programming, preferably using Python, MATLAB, C/C++, or comparable programming languages.

Responsibilities

• Develop advanced computational methods for reliability and robustness assessment of structural and infrastructure systems under uncertainty.
• Develop and implement efficient probabilistic methods for high-dimensional, time-dependent, and dynamic problems, including advanced sampling and surrogate modelling techniques.
• Investigate the use of AI and machine-learning methods to improve the efficiency and scalability of reliability, rare-event, and system-level analyses.
• Apply the developed methodologies to structural and infrastructure-system case studies, including problems involving damage propagation and system robustness.
• Develop, maintain, and document research codes and computational workflows supporting the project.
• Prepare research findings for publication in high-quality international journals and presentation at scientific conferences.
• Contribute to the preparation of research proposals and grant applications.
• Collaborate with members of Lab and external research partners and contribute to related research activities within the lab.
• Supervision of students in relevant topics.

Skills

Python

MATLAB

C/C++

Probabilistic modelling

Machine learning

Education

PhD in Civil Engineering or related field

Tools

SciPy stack

Git

Job description

NTU Singapore, School of Civil and Environmental Engineering, invites applications for a Research Fellow to advance computational reliability methods for structural and infrastructure systems under uncertainty, focusing on high-dimensional probabilistic analysis, surrogate modelling, and AI-enabled techniques.

The role covers developing efficient algorithms, applying methods to case studies, publishing in international journals, and contributing to proposals while supervising students within the