Publisher
source

University of Manitoba

Civil Engineering University of Manitoba in Canada

Degree Level

PhD

Field of study

Data Science

Funding

The positions offer a competitive stipend and full tuition coverage for four years. Additional benefits include access to advanced computing resources, opportunities for interdisciplinary collaboration, and comprehensive professional development such as conference travel, workshops, leadership training, and career mentoring.

Deadline

Expired

Country flag

Country

Canada

University

University of Manitoba

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Keywords

Data Science
Machine Learning
Environmental Science
Agriculture
Geography
Climate Science
Civil Engineering
Earth Science
Water Resource Management
Earth Observation
Climate Resilience

About this position

The Hydroclimate-Society Lab at the University of Manitoba, led by Dr. Donghoon Lee in the Department of Civil Engineering, is recruiting three PhD research assistants for Fall 2026. The lab investigates how climate extremes and long-term changes affect natural systems and human societies, using advanced data and interdisciplinary methods.

Research areas include water management with climate forecasts and satellite data, projecting socio-environmental impacts of extreme heat and wildfires, developing hazard footprints, designing disaster resilience metrics, monitoring crop yield with Earth Observation for early warning, and advancing predictions of crop productivity. Applicants should have a bachelor's degree (master's preferred) in a relevant field, research experience with large-scale datasets, skills in machine learning and programming (Python required), and strong communication abilities.

The positions are fully funded for four years, covering stipend and tuition, and offer access to advanced resources and professional development. Interested candidates should apply via the 2026F-GRA-Research Interest Form by December 15, 2025. Applications are reviewed on a rolling basis.

Funding details

The positions offer a competitive stipend and full tuition coverage for four years. Additional benefits include access to advanced computing resources, opportunities for interdisciplinary collaboration, and comprehensive professional development such as conference travel, workshops, leadership training, and career mentoring.

What's required

Applicants must have a bachelor's degree (master's preferred) in civil or environmental engineering, climate science, geography, agriculture, data science, or related disciplines. Research experience with large-scale Earth science or socioeconomic datasets is required. Experience in machine learning, AI, or deep learning, especially for scientific applications, is expected. Strong programming skills in Python are required, and a GitHub portfolio is highly recommended. Excellent written and oral communication skills are also necessary.

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University Name
Country flag

Canada

Research Interests

Climate Science

Geography

Data Science

Civil Engineering

Climate Resilience