Research Assistant in Flood Mapping/Risk Assessment Using Artificial Intelligence - Research Affiliate Program

Important messages

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Assessment accommodation

Duties

The successful candidate will have the opportunity to conduct research in the fields of GIS, Remote Sensing, Machine/Deep Learning, and Programming for disaster management applications. The focus of this research concerns extracting information from various sensor data (Lidar, satellite, terrestrial scanners, etc) to populate 3D building models. Through the development of automated techniques to characterize and attribute buildings on the ground, e.g. building occupancy, height above first floor, presence/absence of basement, disaster modelling, such as flood risk models, can be populated with this data, and thus be able to provide more accurate estimates of infrastructure risk due to these hazards.

The successful student will have the opportunities to interact with CCMEO staff, researchers and technicians. The day-to-day work will take place at University of New Brunswick (Fredericton campus).

The successful candidate should have a good work ethic, strong sense of responsibilities, and the ability to work in team environments.

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. Duration of the RAP will depend on academic level: Doctorate Students (1-3 years). Extensions may be possible.

Positions to be filled: 1

Information you must provide

Your résumé.

A covering letter "Maximum of 2000 words."

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 Masters or PhD program in Geodesy and Geomatics Engineering, University of New Brunswick (for qualifications please see https://www.unb.ca/fredericton/engineering/depts/gge/graduate/index.html).
- Hold a Bachelor’s or Master’s degree in Geomatics Engineering or a similar field.

Degree equivalency

Experience :
• Experience in analyzing and understanding geospatial data, including optical and/or SAR remote sensing datasets.
• Experience in Machine Learning and Deep Learning applications
• Experience in conducting literature reviews and summarizing information.
• Experience in writing research reports and making scientific presentations.

The following will be applied / assessed at a later date (essential for the job)

English essential

Information on language requirements

Knowledge:
• Computer programming, esp Python
• Knowledge of geomatics
• Knowledge of OGC Standard CityGML

Competencies
• Initiative
• Adaptability
• Teamwork
• Communication and organizational skills

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.

We thank all those who apply. Only those selected for further consideration will be contacted.