Student Research Assistant in Carbon and Wetland Mapping

Student Research Assistant in Carbon and Wetland Mapping
- Research Affiliate Program

Environment and Climate Change Canada
- Landscape Science Division

Closing date:
July 30, 2026 - 23:59, Pacific Time

Reference number
DOE
26J
- Selection process number
_STU_675712 Location
Ottawa (Ontario)
Salary
$18.84 to $38.38 per hour - (Rates of pay are determined at the initial appointment or reappointment stage and are based on the student's current academic level. )
Who can apply
To be considered for Research Affiliate Program (RAP) work opportunities, all candidates must meet the following eligibility criteria by the date of appointment:
- Be recognized as having full-time student status at an accredited Canadian post-secondary academic institution (this includes students with a disability deemed to have full-time status). Individuals pending approval of acceptance or in the process of submitting applications are encouraged to apply, as proof of enrollment will only be required prior to the start date.
- Be enrolled in an academic program that requires research as part of the curriculum.
- Be at least the minimum age to work in the province or territory where the job is located.
Organization information
For further information on the organization, please visit .

On this page

About the position

Duties
The successful candidate(s) will undertake remote sensing research in the National Wildlife Research Centre – Landscape Science Divisions’ geomatics lab. The work will support work under the Natural Climate Solutions project focusing on carbon and wetland mapping. Specifically:

• Assess Earth Observation and bioclimatic predictor variables that can contribute to the identification of wetland ecosystems across Canada, particularly in the sub-arctic and arctic,

• Investigate machine learning classification and regression methodologies

• Designing remote sensing predictor variable testing experiments and preparing research protocols, including scripting, data acquisition, pre-processing, data storage

• Designing bioclimatic predictor variable testing experiments and preparing research protocols, including data acquisition, pre-processing, data storage

• Scripting and refining remote sensing Earth Observation processing and pre-processing as well as machine learning classifications in python and R

• Data analyses and communication of results Intent of the process
This is a student position of 10-20 hours per week, for a 1-year period starting Summer 2026 with opportunity to renew for an additional 1 or 2 years.
Positions to be filled
2 Important messages
To be considered for Research Affiliate Program (RAP) work opportunities, all candidates must meet the following eligibility criteria by the date of appointment:

- Be recognized as having full-time student status at an accredited Canadian post-secondary academic institution (this includes students with a disability deemed to have full-time status). Individuals pending approval of acceptance or in the process of submitting applications are encouraged to apply, as proof of enrollment will only be required prior to the start date.

- Be enrolled in an academic program that requires research as part of the curriculum.

- Be at least the minimum age to work in the province or territory where the job is located.

Conditions of employment

Reliability Status security clearance

Learn more about .

You need (essential for the job)

Your application must clearly explain how you meet the following
Education:
The Student must be currently enrolled or willing to enroll in a graduate MSc program with full-time student status in a relevant field specialization in Remote Sensing, Geomatics, Data Science or Geography.

Proof of enrollment will be required prior to start date and the student must return to full-time studies for your next academic term.

Learn more about .

Experience:

Experience acquiring and processing satellite imagery.

Experience working on Canadian wetlands ecosystems, including northern wetlands (on the job experience).Experience classifying satellite imagery into landcover classes related to wetlands ecosystems.

Experience scripting in Python and R for processing satellite imagery.

Experience…