À propos

The Smart Structural Health Monitoring and Control Lab is inviting applications for a tenure-track or tenured faculty position at the rank of Assistant, Associate, or Full Professor. We are seeking outstanding scholars to lead and advance research at the intersection of machine learning, prediction, and civil engineering applications.

The successful candidate will be expected to develop an independent, externally funded research program focused on data-driven approaches for structural health monitoring, crack detection and analysis, and predictive modeling of civil infrastructure systems. The role will also involve mentoring graduate students, supervising research projects, and contributing to teaching at both undergraduate and graduate levels.

Applicants must hold a PhD in Civil Engineering, Computer Science, Data Science, or a closely related field, with demonstrated expertise in machine learning, statistical modeling, CAD-based structural modeling, and applied mathematics. The ideal candidate will bring a strong publication record in peer-reviewed journals and conferences in the areas of machine learning for structural applications, computational mechanics, or predictive modeling. Evidence of successful interdisciplinary collaborations and experience in securing competitive research funding are highly desirable.

The position offers an attractive salary and benefits package, as well as access to state-of-the-art laboratory and computational resources. Faculty members at SSHMC have the opportunity to engage in cross-disciplinary collaborations, contribute to high-impact research, and influence the future of smart infrastructure monitoring and control.

Interested candidates should submit a CV, cover letter, research statement, teaching philosophy, and names of three references to:
📧 qianqian.li@lecnam.net

📌 Subject: Faculty Application – SSHMC LAB

The Smart Structural Health Monitoring and Control Lab is seeking motivated Master’s students for an internship in the area of machine learning and prediction for civil engineering applications. The project focuses on developing and applying computational tools for crack detection, analysis, and prediction in structural systems, contributing to safer and more resilient infrastructure.

Candidates should have a strong background in programming (Python, MATLAB, or similar), CAD modeling, and applied mathematics. Familiarity with machine learning algorithms, statistical modeling, and data analysis is highly desirable. Students from Civil Engineering, Computer Science, Data Science, or related disciplines are welcome to apply.

This internship provides an excellent opportunity to gain hands-on research experience in a stimulating environment and to contribute to cutting-edge projects.

Applicants should send their CV to:
📧 qianqian.li@lecnam.net

📌 Subject: Internship Candidate for SSHMC LAB

The Smart Structural Health Monitoring and Control Lab is seeking a highly motivated Postdoctoral Researcher to contribute to cutting-edge projects in the field of machine learning applications for civil engineering. The successful candidate will work on developing and optimizing advanced computational tools to detect, analyze, and predict structural damage, with a particular focus on crack identification and propagation in civil infrastructure.

The position requires a strong background in machine learning, statistical modeling, and data-driven prediction techniques, coupled with expertise in programming, computer-aided design (CAD) modeling, and applied mathematics. The candidate will be expected to design novel algorithms, implement robust analytical pipelines, and validate methods using both simulated and experimental structural data.

Applicants should hold a PhD in Computer Science, Civil Engineering, or a closely related discipline, with a proven record of research in machine learning, structural modeling, or computational methods. A deep understanding of ML algorithms, statistical inference, and research methodologies is essential. Strong programming skills (e.g., Python, MATLAB, or similar), familiarity with CAD tools, and the ability to handle large datasets are required. Previous experience in civil engineering applications or interdisciplinary projects will be considered an asset.

The role offers a stimulating research environment with opportunities to collaborate across disciplines and contribute to impactful innovations in structural health monitoring and control. The position comes with an attractive salary package and access to state-of-the-art laboratory facilities.
Interested candidates should submit their CV and the names of two references to:
📧 qianqian.li@lecnam.net

📌 Subject: Candidate for SSHMC LAB