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As part of a project supported by the Ministère de la SecuritéÌýPublique du Québec, the student will be involved in the complete chain of calculation of annualized earthquake losses (AEL) for a number of selected regions. The calculations will be carried out using the HAZUS tool, which is constantly being developed by the US Federal Emergency Management Agency (FEMA) and follow the FEMA P-366 method.
The student will have to work with data on demographics, buildings and site conditions. The seismic values will be calculated using the Canadian Seismic Hazard Model 2020 linked to the OpenQuake engine.

- Literature review on the following topics
- Creation and integration of the dataset for each study region into Hazus
- Calculation of the hazard in Openquake
- Calculation of the loss for 11 return periods and estimation of the AEL
- Mapping the results
- Writing a report with all the results:
- General context of the study
- Aims of the work
- Data collection and interpretation
- Findings
- Discussion
- Bibliography

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It is now known that antimicrobial resistance can arise in farm animals and in humans that are treated by antimicrobials, and in the environment when antimicrobial residuals are discharged. Then, antimicrobial resistance spread from their original source to humans in part by accumulating in the gut microbiota. The goal of this project is to determine the factors determining the rate of transfer of antimicrobial resistance from wastewater to the human gut microbes. To do so, laboratory-scale reactors simulating the gut conditions will be operated with different food types and exposed to wastewater microbes. Molecular biology and genomic techniques will be used to track the establishment of resistance genes in the simulated gut microbiota. The SURE intern will be assisting a PhD student in conducting these experiments. They will be responsible for reactor maintenance and performing test to assess the reactors'Ìýbehaviours. They will also be introduced to molecular techniques.

Perform the daily maintenance and sampling of the laboratory-scale reactors. Perform laboratory analyses to determine physico-chemical characteristics of samples. Contribute to computer data entry and trend analyses.

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The spread of antimicrobial resistance through environmental and human-associated microbes threatens to reduce the efficacy of medical treatment. One of the main sources of resistance in the environment is the release of bacteria from municipal wastewater treatment facilities. After disposal of treated wastewater and waste biosolids, the resistance genes rejected in the environment migrate back to humans via the consumption of foods and water. Therefore, tracking the various resistance genes in different environments is necessary to evaluate the risk of migration backs to humans. Our research group is developing a new approach based on PCR amplicon sequencing to achieve this with a high sensitivity. The goal of the project is to perform validation tests on the PCR primer sets that perform the detections. This will involve performing molecular manipulations in the lab and cultivation of environmental microbes. The PCR primers will then be applied to the analysis of antimicrobial resistance genes present in the microbial communities sampled in different environments. Thus, part of the project may entails helping with field sampling.

Perform analyses of antimicrobial resistance genes in environmental and man-made using a suite of molecular (DNA or RNA based) and chemical analysis techniques in the lab. Cultivation of environmental microbes. Sampling surface water and wastewater in the field.

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Reducing the carbon footprint of the transportation section is being approached by an increase in the percentage of electric vehicles. Powering these vehicles requires the generation of more electric power from renewable energy sources, from which electricity is generated intermittently. This create a demand for energy storage to balance the supply and demand of the electricity. The increase in electricity demand from the increasing EV fleet will be determined and the required versus existing energy storage in hydropower facilities will be determined for different provinces.

1) Determine the increased electricity demand based on the projected increases in the size and number of vehicles in the EV fleet.
2) Estimate the existing hydropower storage and compare to the projected demand.

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The goal of a circular economy is to transition from our predominantly linear system – from materials extraction to product use to landfill or incineration – to circular, where materials are always resources, never waste. Consequences of circular economy solutions must be measured against their linear counterparts to avoid unintended externalities, burden shifting, or higher economic costs. Life cycle assessment (LCA) quantifies environmental impacts of potential solutions from the extraction of raw materials through to waste disposal. There are a growing number of tools that combine circular economy and LCA approaches, yet Canadian research remains scarce. The first position will focus on reviewing existing models and developing concepts for Canadian models that support energy infrastructure contributing to net zero emissions.
The second of two positions will support the development of energy systems models that examine how to reach net-zero emissions and quantify life cycle impacts. Such models comprise all parts of the energy infrastructure supply chain, from primary resources through all processes that transform, transport, distribute and convert energy into the supply that meets the demand of consumers. The student will be offered the opportunity to work on collecting and improving a section of the model data inputs, chosen in discussion with a postdoctoral fellow and the supervising professor.
The Energy Technology And Policy Assessment (ETAPA) research group focuses on developing life cycle, circular economy, techno-economic and systems solutions that examine the full portfolio of energy options in support of more sustainable environmental outcomes.

Each student will focus on one of the outlined research tasks and produce the noted deliverables.

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Methane is a potent greenhouse gas and reducing its emissions can substantially combat global warming in the short term. Measurements have shown that abandoned oil and gas wells are sources of methane to the atmosphere. The project involves conducting one or more field trip(s) to oil and gas-producing regions, analyzing the results in the laboratory, and conducting data analysis. Various methods including flux chambers and mobile instruments will be used to measure methane flow rates and other geochemical parameters. The findings from this study will provide quantitative data for evaluating and designing mitigation solutions for the tens of millions of abandoned oil and gas wells around the world.

Prepare for one or more field sampling trip(s), conduct field sampling, and analyze data.

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Methane is a potent greenhouse gas and reducing its emissions can substantially combat global warming in the short term. Measurements have shown that natural gas distribution, landfills, and wastewater systems are sources of methane to the atmosphere. The project involves preparing one or more field trip(s) in multiple cities, conducting field measurements, analyzing the results in the laboratory, and analyzing the data. Various methods including flux chambers and mobile instruments will be used to measure methane flow rates and other geochemical parameters. The findings from this study will provide quantitative data for evaluating and designing mitigation solutions for methane emissions from cities.

Prepare for one or more field sampling trip(s), conduct field sampling, and analyze data.

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The project seeks to inform, with experimental data, the design we have developed so far for a low-cost timber retrofit that improves structural and thermal performance of existing masonry walls.

The successful candidate will be trained on small-scale experimental testing of timber and masonry specimens, and perform:

-monotonic compressive tests
-monotonic flexural tests
-monotonic shear tests
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The project aims to test the shrinkage and expansion behavior of concrete and clay masonry, respectively, but also freeze-thaw, to estimate how climate change may affect masonry structures.

The successful candidate will be trained on small-scale experimental testing of masonry specimens, and perform:

-frost dilatometer tests
-freeze-thaw tests
-expansion and shrinkage tests
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Construction is a labor-intensive and low-efficiency industry, which is suffering from labor shortage issues. Concrete is the most used construction material in the world and rebar assembly is the most labor intensive work in the concrete structure construction process. The PI's research group is leading a large project to automate the rebar assembly process. The SURE intern will assist with this large project by helping conduct literature review, collect database, and train deep learning models.

Conducting literature review
Collecting database
Training of deep-learning models

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Canada has several seismic zones with different types of earthquakes. Destructive earthquakes have occurred in the past and are anticipated to happen in the future. In response to this seismic risk, Natural Resources Canada has developed the Sixth Generation Seismic Hazard Model of Canada. This model has been integrated into the 2020 National Building Code of Canada (NBCC). The seismic design provisions outlined in the 2020 NBCC specify the earthquake ground motions for which structures should be designed, expressed as a uniform hazard spectrum (UHS) with a 2% probability of exceedance in 50 years. The UHS is contingent upon the specific structure location and site conditions. In certain applications, such as dynamic analysis using time history methods, having representative time histories of expected earthquake motions is crucial. However, the scarcity of historical devastating earthquakes in Canada poses a challenge in obtaining a substantial number of recorded motions that match the 2020 NBCC target spectra across a wide period range. Therefore, there is a need to generate synthetic ground motions to facilitate the design and analysis of both new and existing structures. This project aims to leverage recent advances in machine learning and signal processing techniques to generate synthetic earthquake ground motions tailored to specific seismic regions in eastern and western Canada.

1. Identify the potential impact and usefulness of artificial ground motions.
2. Identify the similarities and differences between earthquake, music, and other types of time series signals.
3. Literature review of existing engineering-based and data-driven methods, as well as the performance criteria, for generating artificial ground motions.
4. Literature review of signal processing techniques for generating different types of music signals.
5. Identify potentially feasible machine/deep learning techniques that can generate artificial ground motions through data fusion of different types of time series signals.

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This project focuses on harnessing generative artificial intelligence (AI), including multi-modal large language models like Gemini and ChatGPT, to address the evolving challenges in urban transportation. It integrates AI with diverse data sources, including surveys, traffic data, and infrastructure and environmental information, aiming to enhance our understanding of travel behaviors, envision future urban scenarios, and design innovative shared automated mobility systems. The project specifically utilizes generative AI, especially large language models and image generators, to understand and synthesize individual behaviors and generate a variety of urban scenarios, both routine and disruptive. This multifaceted approach provides a broad view of potential future challenges in urban mobility, from natural disasters to significant urban changes. The research also involves using AI-generated scenarios to develop and refine adaptable, efficient, and user-friendly shared automated mobility services. This project aims to impact the design of sustainable and resilient mobility systems for future urban environments, contributing to the fields of engineering, urban planning, and AI.

1. Propose innovative use and methods of AI technologies, especially large language models, to understand and simulate individual behaviors and envision urban scenarios.
2. Gather and integrate data from varied sources and types.
3. Develop and refine shared automated mobility services and evaluate them in various AI-generated scenarios.
4. Create prototypes of the novel usage and methods and conduct testing.

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