PhD position: Global Watershed Hydrologic Function, University of British Columbia
- Vancouver, BC, Canada
- Greater Vancouver Metropolitan Area, Canada
Internship
Applications open in a new tab.
Job details
- Job type
- Internship
- Apply by
- Posting language
- English
- Posted
Original job description
University of British Columbia (UBC) in Vancouver, , Canada
Apply before: 6 December 2026
Position
Posting:
PhD position
Apply Before
6 December 2026
A PhD position is available under the supervision of Dr. Ali Ameli in the Department of Earth, Ocean and Atmospheric Sciences at the University of British Columbia (UBC), Vancouver, Canada.
Project: This funded project studies global watershed hydrologic function: how watersheds collect, store and release water across many types of landscape, from forested and mountainous to wetland, agricultural and urban. The student will identify global patterns in hydrologic function and how it varies over time, from event to event, season to season and year to year. The work combines large-sample hydrology, data science, machine learning and process-informed deep learning with conceptual and process-based hydrologic models.
Please review our publications to get to know our work and the type of research we do before applying: https://hgs4wm.eoas.ubc.ca/publications
Qualifications: A master's degree in hydrology, water resources or a related discipline, with a strong background in data science and machine learning and in conceptual and process hydrology.
Start date: September 2027
How to apply: Email the following to Hgs.wm.contact@gmail.com, with the subject line "PhD Application: Global Watershed Hydrologic Function":
Please feel free to share this opportunity with potential applicants.
Ali Ameli
Associate Professor, Department of Earth, Ocean and Atmospheric Sciences
The University of British Columbia, Vancouver, Canada
Of interest for:
Apply before: 6 December 2026
Position
Posting:
PhD position
Apply Before
6 December 2026
A PhD position is available under the supervision of Dr. Ali Ameli in the Department of Earth, Ocean and Atmospheric Sciences at the University of British Columbia (UBC), Vancouver, Canada.
Project: This funded project studies global watershed hydrologic function: how watersheds collect, store and release water across many types of landscape, from forested and mountainous to wetland, agricultural and urban. The student will identify global patterns in hydrologic function and how it varies over time, from event to event, season to season and year to year. The work combines large-sample hydrology, data science, machine learning and process-informed deep learning with conceptual and process-based hydrologic models.
Please review our publications to get to know our work and the type of research we do before applying: https://hgs4wm.eoas.ubc.ca/publications
Qualifications: A master's degree in hydrology, water resources or a related discipline, with a strong background in data science and machine learning and in conceptual and process hydrology.
Start date: September 2027
How to apply: Email the following to Hgs.wm.contact@gmail.com, with the subject line "PhD Application: Global Watershed Hydrologic Function":
- A one-page cover letter explaining how your expertise relates to global watershed hydrologic function
- CV
- Transcripts from bachelor's and master's degrees
Please feel free to share this opportunity with potential applicants.
Ali Ameli
Associate Professor, Department of Earth, Ocean and Atmospheric Sciences
The University of British Columbia, Vancouver, Canada
Of interest for:
- Terrestrial Working Group
- Hydrology Focus Research Group
More about this job
Responsibilities
Identify global patterns in watershed hydrologic function across diverse landscapes and examine how these patterns vary between events, seasons, and years. Combine large-sample hydrology, data science, machine learning, process-informed deep learning, and conceptual and process-based hydrologic models.
Requirements
A master's degree in hydrology, water resources, or a related discipline is required. Applicants should have a strong background in data science, machine learning, and conceptual and process hydrology.
Skills
- Hydrology
- Water Resources
- Data Science
- Machine Learning
- Large-Sample Hydrology
- Deep Learning
- Conceptual Hydrologic Modeling
- Process-Based Hydrologic Modeling
- Watershed Hydrologic Function
Visa sponsorship
Not detected in the job text
Hiring contact
Ali Ameli
Categories
- Science & Research
- Environmental & Sustainability
- Data & Analytics
- Education
Keywords
- Global Watershed Hydrologic Function
- Hydrology
- Water Resources
- Watersheds
- Large-Sample Hydrology
- Data Science
- Machine Learning
- Process-Informed Deep Learning
- Conceptual Hydrologic Models
- Process-Based Hydrologic Models
- Hydrologic Function
- Water Collection
- Water Storage
- Water Release
- Forested Landscapes
- Mountainous Landscapes
- Wetlands
- Agricultural Landscapes
- Urban Landscapes
- Temporal Variability
- Earth, Ocean and Atmospheric Sciences