Our climate is changing in ways that will directly impact our drinking water quality. The water research group at UBCO is trying to understand how shifting climate patterns will affect source waters and what that means for the infrastructure we rely on.
I am looking for 1-2 motivated graduate students (PhD and MASc) to join an industry-supported project focused on modeling how water quality will change under different climate change scenarios. We have a wealth of historical data from our utility partners, and we are now at the stage of asking how this data can be used to make proactive and informed decisions regarding major capital upgrades or operations.
This project sits right at the intersection of water science and data science. I don’t expect any single candidate to be an expert in everything, but I am very interested in meeting people who are excited to bridge these gaps. Specifically, we are looking for team members with a background (or a deep desire to learn) in:
- Computer Science & Machine Learning: Experience with data science, time-series forecasting, and developing AI models using Python.
- Environmental & Civil Engineering: Knowledge of drinking water treatment processes and source water quality dynamics.
- Climate Change Modelling: Background in working with climate projections, weather generators, and scenario analysis.
- Infrastructure Assessment: Experience or interest in evaluating civil infrastructure vulnerabilities and risk assessment.
If this sounds like a fit for your interests, candidates are invited to send a 1) a 1-page summary of motivation and expertise related to the project, and 2) a current CV to nicolas.peleato@ubc.ca.
I’m looking forward to learning more about your work and your ideas.