Opportunities

For the recent postdoctoral fellow position, refer to here.

The RILCIE group keeps recruiting self-motivated researchers at all levels (undergraduate, masters, PhD and post-doctoral fellow) from time to time. Young researchers looking for research opportunities are encouraged to contact Dr. Arnold Yuan via email (arnold dot yuan at ryerson dot ca).

The recruitment focus for year 2022 is on infrastructural resilience, infrastructure asset management, structural reliability, and legal case analysis for construction lawsuits:

  • Infrastructure resilience – Focusing on impact of climate change and multiple hazards on infrastructure planning, design, operations and management. Applicants are expected to have a good demand of engineering risk and reliability and at least one of the following infrastructure systems: building structures, earthquake engineering, pavement structures, bridges, municipal pipes, transportation network, oil and gas pipelines.
  • Infrastructure asset management — Applicants are expected to have good knowledge of materials, design and life-cycle activities of one of the following asset types: pavements, bridges, municipal pipes, oil and gas pipelines. Candidates are expected to work on stochastic degradation modelling, lifecycle costing analysis, and network optimization.
  • Use of natural language processing for legal case analysis in construction litigation — Applicants must have a solid background on construction management. Experience with claims and dispute resolution will be a good asset.
  • Structural reliability I – There are two thrusts: progressive collapse design of concrete structures and lifecycle pavement analysis and design. Applicants are expected to have a solid background on either nonlinear analysis of concrete structures or mechanistic-empirical pavement design (MEPDG). Proficiency in OpenSEES or AASHTOware Pavement ME Design will be a good asset. Surrogate modelling and lifecycle optimization are the research focus.
  • Structural reliability II – This theme focuses on probabilistic structural integrity assessment and management for components, structures and systems of nuclear power generation stations. High-performance computing, uncertainty analysis, and decision making under uncertainty are the primary research topics.

For all themes, applicants are expected to have a solid command on MATLAB, Python or R.

When you send your first inquiry email, please (1) indicate which research theme you would like to work on, (2) identify at least three major active researchers (not your references) in the world, and (3) explain why you choose Ryerson and me for further study. General inquiries that do not include those elements will NOT be responded to.

Latest updated on March 24, 2022