Sara Sadri
3 months ago
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PhD Opening in Environmental Data Science, AI, Remote Sensing and Geospatial Analytics University of Prince Edward Island in Canada
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Country
Canada
University
University of Prince Edward Island

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About this position
The HydroTerra Lab at the University of Prince Edward Island is seeking a highly motivated PhD student in Environmental Data Science.
Led by Dr. Sara Sadri (Canada Research Chair in Remote Sensing and Water Security; Associate Professor), the project sits at the intersection of artificial intelligence, Earth observation, geospatial analytics, remote sensing, and environmental science.
The successful candidate will work with large-scale environmental, geospatial, and satellite datasets to develop and apply advanced analytical approaches. The role is especially suitable for applicants interested in machine learning, quantitative modelling, GIS, and data-driven solutions to real-world environmental challenges.
Eligible backgrounds include an MSc in Computer Science, Civil Engineering, Environmental Engineering, Agricultural Engineering, Hydrology, Geography, Remote Sensing, Mathematics, or a closely related quantitative field.
Applicants should have strong programming skills in R and/or Python, experience with statistical modelling, machine learning, geospatial analytics, or large-scale environmental datasets, and familiarity with remote sensing, GIS, Earth observation, environmental modelling, or quantitative analysis. Strong research experience and scientific writing ability are also expected.
Interested candidates should email a CV, transcripts, a brief statement of research interests, and two references to [email protected] with the subject line PhD Opportunity Inquiry – Environmental Data Science. Selected candidates will be invited to apply through the University of Prince Edward Island's official graduate admissions process.
Applications are reviewed on a rolling basis until the position is filled.
Funding details
Available
What's required
Applicants should have an MSc in Computer Science, Civil Engineering, Environmental Engineering, Agricultural Engineering, Hydrology, Geography, Remote Sensing, Mathematics, or a closely related quantitative discipline. Strong programming skills in R and/or Python are required, along with experience in statistical modelling, machine learning, geospatial analytics, or large-scale environmental datasets. Familiarity with remote sensing, GIS, Earth observation, environmental modelling, or quantitative analysis is preferred. Candidates should demonstrate strong quantitative, analytical, and problem-solving skills, research experience, scientific writing ability, and the ability to work independently while contributing to collaborative projects. Preference is given to candidates with experience in quantitative modelling, machine learning, geospatial analysis, remote sensing, or environmental data science, especially those based in Canada, the United States, or Europe.
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