Don't miss our weekly PhD newsletter | Sign up now Don't miss our weekly PhD newsletter | Sign up now

This project is no longer listed on FindAPhD.com and may not be available.

Click here to search FindAPhD.com for PhD studentship opportunities
  Prof Gabriel Fabien-Ouellet  Applications accepted all year round  Funded PhD Project (Students Worldwide)

About the Project

The National Building Code requires the study of the local seismic effects of any new large building. The use of seismic auscultation methods is an essential part of this work: they make it possible to estimate the shear wave velocity of the ground, a physical property directly related to the local site effects during an earthquake. Seismic surveys are acquired daily for this purpose across Canada by geotechnical engineering teams. However, the reliability and precision of these auscultation methods remain limited, in particular because processing methodologies are too simplistic. This often results in the need for further testing, which increases costs.

A doctoral or master's candidate is sought to improve seismic survey processing and acquisition techniques. To free ourselves from the assumptions limiting traditional approaches, the candidate will use the latest advances in deep learning. Concretely, deep neural networks will be trained to discern the seismic signals allowing the prediction of soil velocity profiles. To do this, we will work with our business partners who provide us with a large database of seismic recordings, necessary for training the networks. The candidate will work in partnership with our partners to acquire new data and optimize acquisition protocols for neural processing.

Why join the project? You will have the chance to work directly with our partners to develop your field expertise in geophysics, applied to the field of geotechnics. You will also develop your expertise in data processing, particularly in deep learning, a highly sought-after profile on the job market. Finally, you will join a dynamic team that works to advance engineering and the environmental geophysics.


Computer Science (8) Engineering (12) Geology (18)
Search Suggestions
Search suggestions

Based on your current searches we recommend the following search filters.

 About the Project