PhD Position in Large-Scale Hydrology: The University of Waterloo is offering a PhD position in the Department of Earth and Environmental Science, focusing on developing and applying computational approaches to tackle complex problems in large-scale hydrology. The successful candidate will have the opportunity to work on hydrological modeling, flood risk assessment, water resource management, and climate change impacts on water systems using machine learning-based and process-based models.
PhD Position in Large-Scale Hydrology – Focus on Computational Methods
Designation
PhD in Large-Scale Hydrology
Research Area
- Developing and applying advanced computational methods and models for large-scale hydrological analysis
- Utilizing machine learning, data assimilation, or other computational techniques to improve hydrological models and predictions
- Improving hydrologic processes and process understanding in models
- Working with large datasets from remote sensing, climate models, and in-situ measurements
- Developing components of the open-data portal HydroHub.org to facilitate communication of simulation results and make models available to users
- Developing automated workflows used on the open-data portal to enable users to obtain model setups, calibrated models, and simulations of multi-model ensembles
- Collaborating with a multidisciplinary team including hydrologists, environmental scientists, and computational experts
Location
Department of Earth and Environmental Science, University of Waterloo, Waterloo, ON, Canada
Eligibility/Qualification
- Master’s degree (or equivalent) in computer science, applied mathematics, environmental engineering, or a related field
- Strong background in computational methods, including machine learning, statistical modeling, high-performance computing, data assimilation, and/or open-data portal generation
- Programming skills in languages such as Python (highly preferred), bash (preferred), Fortran, C/C++, R, MATLAB, or similar
- Solid understanding of software development principles, version control systems, and debugging techniques
- Excellent problem-solving skills and the ability to troubleshoot complex code-related issues
- Excellent communication and writing skills in English
- Self-motivated with a strong commitment to delivering high-quality results within designated timelines
Description
The PhD student will have the opportunity to:
- Develop and apply advanced computational methods and models for large-scale hydrological analysis
- Utilize machine learning, data assimilation, or other computational techniques to improve hydrological models and predictions
- Improve hydrologic processes and process understanding in models
- Work with large datasets from remote sensing, climate models, and in-situ measurements
- Develop components of the open-data portal HydroHub.org to facilitate communication of simulation results and make models available to users
- Develop automated workflows used on the open-data portal to enable users to obtain model setups, calibrated models, and simulations of multi-model ensembles
- Collaborate with a multidisciplinary team including hydrologists, environmental scientists, and computational experts
- Present research findings in academic journals and conferences
How to Apply
Please submit your application as a single PDF to Julie Mai. Please include “PhD position in Large-Scale Hydrology” in the subject line for any email communication.
Last Date to Apply
Applications will be reviewed as they are received, and the positions will remain open until filled.
