Research project title
Reliability-Based and Data-Driven Frameworks for Performance-Based Safety Assessment of Water-Retaining Structures
Education level
Doctorate
Director/co-director
Director: Rocio Lilen Segura
End of display
February 6, 2026
Areas of expertise
Learning and inference theories
Primary sphere of excellence in research
Sustainable Transport and Infrastructures
Secondary sphere(s) of excellence in research
Modeling and Artificial Intelligence
Unit(s) and department(s)
Department of Civil, Geological and Mining Engineering
Conditions
How to apply Interested students are invited to email me at rocio-lilen.segura@polymtl.ca with:
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CV
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Transcripts
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A 1-page description of their background and research interests
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Names and contact info of 3 referees
Detailed description
Project focus
The PhD will work on reliability-based and performance-based assessment of critical infrastructure, with a strong emphasis on dams and water-retaining structures. The goal is to move beyond traditional deterministic safety factors toward probabilistic, data-driven and decision-oriented frameworks that better reflect uncertainty, failure modes, and real operating conditions.
The research will address challenges that are highly relevant to industry, including:
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How to interpret very small probabilities of failure in practice
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How to prioritize investigations, testing, and monitoring using risk and cost-benefit analysis
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How to use advanced numerical models, simulations, and AI/ML tools to understand what really drives structural risk
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How to make safety and rehabilitation decisions that are transparent, rational, and defensible
Who should apply?
I'm looking for candidates with a background in structural engineering and a strong interest in one or more of the following areas:
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Reliability and risk analysis
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Computational and numerical modeling
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Machine learning / AI for engineering applications
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Probabilistic methods and uncertainty quantification
Financing possibility
Fully funded
