Research Fellow: AI-Powered Reliability for Infrastructure

Nanyang Technological University; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

NTU Singapore’s School of Civil and Environmental Engineering invites applications for a Research Fellow to advance computational methods for reliability and robustness assessment of structures and infrastructure under uncertainty. You will develop efficient probabilistic techniques and surrogate models, and explore AI/ML to scale analyses.

Suitability requires a PhD in a related field, strong background in structural reliability and uncertainty quantification, and experience with Python,

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.

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 Lab members and external research partners; supervise students in related topics.

Skills

Python

MATLAB

C/C++

Uncertainty quantification

Structural reliability

Education

PhD in Civil Engineering or closely related field

Tools

Git

NumPy/SciPy

Job description

NTU Singapore’s School of Civil and Environmental Engineering invites applications for a Research Fellow to advance computational methods for reliability and robustness assessment of structures and infrastructure under uncertainty. You will develop efficient probabilistic techniques and surrogate models, and explore AI/ML to scale analyses.

Suitability requires a PhD in a related field, strong background in structural reliability and uncertainty quantification, and experience with Python,