Reference number: RSN25J-098595-000897
Selection process number: 2025-RSN-EA-RAP-SPI-659498
Natural Resources Canada – Geoscience and Earth Monitoring Sector – Canada Centre for Mapping and Earth Observation
Ottawa (Ontario)
This is a student position of 15-20 hours per week. The hourly salary varies depending on the level of experience and (or) education, according to the Treasury Board student rates of pay. Payments will be made in equal installments three times per year.
For further information on the organization, please visit Natural Resources Canada
Canada Centre for Mapping and Earth Observation
For further information on the Research Affiliate Program, please visit Research Affiliate Program
For further information on the rates of pay, please visit Student rates of pay
Closing date: 17 October 2025 – 23:59, Pacific TimeWho can apply: Persons residing in Canada, and Canadian citizens and Permanent residents abroad.
You are eligible for this program if you meet these 3 requirements:
1. You are a full-time student in a post-secondary institution
3. You are enrolled in an academic program that requires research as part of your curriculum
2. You meet the minimum age required in the province/territory of work
Important messages
We are committed to providing an inclusive and barrier-free work environment, starting with the hiring process. If you need to be accommodated during any phase of the evaluation process, please use the Contact information below to request specialized accommodation. All information received in relation to accommodation will be kept confidential.
Duties
This RAP work is supported by the Flood Hazard Identification and Mapping Program (FHIMP) of Natural Resources Canada. The successful candidate will have the opportunity to conduct research in the fields of AI-powered geospatial data analytics to map post-wildfire flood risk using different data sources, e.g., burned severity map, post-wildfire debris maps, land-cover maps, high-resolution 3D land surface information, soil information, and rainfall intensity information. The focus of this RAP research work will be on the development of AI-powered predictive models to map flood risk using multi-source geospatial data, involving geospatial data preparation, data fusion, as well as spatial-temporal AI methodology in risk prediction applications.
The successful candidate is expected to have good experience in computer programming, Python and Pytorch, spatial-temporal models, geospatial data science, and remote sensing.
In order to be considered, the candidate’s application must clearly explain how she/he meets the following essential qualifications.
Work environment
The analysis and research work will be conducted at the successful candidate’s university.
Intent of the process
Student will be hired through the Research Affiliate Program (RAP) with the purpose to accomplish research and complete a thesis or dissertation. The duration of the RAP will be one (1) year, with possibility of extension depending on academic level.
Positions to be filled: 1
Information you must provide
Your résumé.
A covering letter “maximum 2000 words including proposed research concept, publications and conference attendance if any. Please include a copy of academic transcripts.”
Contact information for 2 references.
A list of the courses you have taken as well as any courses that you are taking now, or that you will be taking this academic year
In order to be considered, your application must clearly explain how you meet the following (essential qualifications)
Education:
Currently enrolled or eligible to enroll in a MSc or Doctorate program at a Canadian University.
A minimum Bachelor of Science degree and study/fieldwork experience related to geosciences, such as Geomatics, Software Engineering, Earth Sciences.
Experience:
• Strong computer programming experience in the design of pipelines/workflows for processing geospatial data;
• Strong experience with Python and pytorch to implement different deep learning models;
• Relevant experience in spatial-temporal predication models for environmental mapping, e.g., air quality, flood risk, and wildfire risk prediction;
• Experience with 3D environmental modeling;
• Experience in geospatial data analytics;
The following will be applied / assessed at a later date (essential for the job)
English essential
Information on language requirements
Knowledge:
• Knowledge of computer programming
• Knowledge of deep learning and spatial-temporal prediction models
• Knowledge about how to use geospatial data for flood risk assessment
Competencies:
• Interactive communication
• Initiative
• Research report writing skills.
The following may be applied / assessed at a later date (may be needed for the job)
Selection may be limited to members of the following Employment Equity groups: Aboriginal persons, persons with disabilities, visible minorities, women
Information on employment equity
Conditions of employment
Reliability Status security clearance – Each student hired through the Research Affiliate Program (RAP) must meet the security requirements of the position as a condition of employment. Therefore, the student will be asked by the hiring organization to complete security-related documents.
Other information
The Public Service of Canada is committed to building a skilled and diverse workforce that reflects the Canadians we serve. We promote employment equity and encourage you to indicate if you belong to one of the designated groups when you apply.
Information on employment equity
Preference
Preference will be given to Canadian citizens and permanent residents, with the exception of a job located in Nunavut, where Nunavut Inuit will be appointed first.
We thank all those who apply. Only those selected for further consideration will be contacted.
Contact information
| Krystia Herbert, Human Resources Advisor, Staffing Operations |
|---|
| krystia.herbert@nrcan-rncan.gc.ca |
Date modified: 2025-09-16
