Reference Number
RSN23J-084208-000045
Selection Process Number
2023-RSN-EA-LMS-577512
Organization
Natural Resources Canada
Year
2023-2024
Days Open
6
Classification
City
Quebec
Type
External
Total
0
Employment Equity
0
(0%)
Screened out
0
(0%)
Screened in
0
(0%)
Employment Equity 0% 0
Screened Out 0% 0
Screened In 0% 0
Women 0% 0
Visible minority 0% 0
Indigenous 0% 0
People with disabilities 0% 0
English 0% 0
French 0% 0
Citizens 0% 0
Permanent Residents 0% 0
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.
As part of a federal research project on sustainable development of surface and groundwater resources, the proposed PhD project aims to develop and apply an artificial intelligence-based modeling framework for water resources. This project is part of an innovation approach to provide decision-making bodies with functional approaches for decision-making. The overall objectives of the project are therefore divided into two phases. First, the development of a conceptual framework that describes the inputs and outputs of the learning machine, as well as the functions that allow it to model subsurface flow in the manner of a physical hydrogeologic model. Care should also be taken in selecting the most appropriate algorithms for the type of problem being solved, based on the available literature. If this is not the case, adjustments and/or algorithmic developments must be considered. This framework will then be tested against existing data sets at well-documented sites for which conventional hydrogeologic models exist. This will allow a comparative analysis of the performance of the different approaches (statistical versus physical). This phase may also include generalization of the learning engine to other hydrogeologic contexts.
At Natural Resources Canada, a Federal government job means developing leadership skills, fostering teamwork, and supporting creativity and innovation. Canada's governments depend on geoscience to inform policy, manage the country's landmass and develop its natural resources responsibly. The Geological Survey of Canada (GSC) is the national organization for geoscientific information and research. Since 1842 the Geological Survey of Canada has produced cutting-edge, authoritative geoscience to support mineral exploration, climate change research, marine and coastal resilience, and natural hazards mapping. Our work supports decision-making in the mining and energy sectors, as well as national sovereignty, hazards risk management and more. The GSC is proud to create a workplace that supports an accessible, equitable, inclusive, and diverse workforce at the ready to tackle current and future science challenges. The GSC provides a stimulating work environment with a passionate team and promotes work-life balance.
The intention is to staff one student position for the completion of a PhD - DOCTORAL PROJECT AIMED AT DEVELOPING AND APPLYING A WATER RESOURCES MODELING FRAMEWORK BASED ON ARTIFICIAL INTELLIGENCE.
Positions to be filled: 1
Your résumé.
A covering letter "250 words max. demonstrating your motivation for this opportunity"
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
Education:
• The candidate must currently have a master’s degree in Geology or Earth sciences from a recognized Canadian or foreign university.
• The candidate must demonstrate his/her motivation on pursuing graduate studies.
Experience/knowledge:
In the context of student recruitment in the federal public service, experience/knowledge can be acquired through studies, work experience or volunteer activities.
• Experience/knowledge of basic earth science disciplines and physical hydrogeology.
• Advanced experience/knowledge of scientific programming.
• Advanced and relevant experience/knowledge in data acquisition, processing, and analysis in artificial intelligence.
English or French
Information on language requirements
Abilities:
• Ability to communicate effectively within the team and with co-workers.
• Ability to work alone and as part of a team.
• Ability to communicate results effectively.
Personal Suitability:
• Motivation
• Autonomy
• Integrity and professionalism
• Diligent
Selection may be limited to members of the following Employment Equity groups: Aboriginal persons, persons with disabilities, visible minorities, women
Information on employment equity
The Department of Natural Resources Canada is committed to having a skilled and diversified workforce representative of the population we serve. In support of our strategy to achieve employment equity goals, selection may be limited to candidates self-identifying as belonging to one of the following Employment Equity groups: women, Aboriginal persons, persons with a disability, and members of visible minority groups.
• Reliability Status security clearance - NOTE: 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.
• The student will need to be enrolled at l'Institut national de la recherche scientifique (INRS, Quebec) for this PhD degree, where his director is located.
• This PhD is conditional on obtaining funding from the research project.
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
We thank all applicants for their interest in our position(s). For the purpose of this staffing process, only candidates selected for further assessment will be contacted.
For further information on the Research Affiliate Program (RAP), please visit:
https://www.canada.ca/en/public-service-commission/jobs/services/recruitment/students/research-affiliate-program.html
Successful completion of both a RAP work assignment and your educational program may lead to a temporary or permanent federal public service position for which you meet the merit criteria and conditions of employment.
For this selection process, it is our intention to communicate with candidates via email. Candidates must include a valid email address in their application. It is the candidate’s responsibility to ensure that this address is functional and that it accepts messages from unknown users (some email systems block these types of email).
A written examination may be administered.
An interview may be administered.
Reference may be sought.
You must provide proof of your education credentials. Transcripts and a list of courses may be required.
Candidates with foreign credentials must provide proof of Canadian equivalency. Consult the Canadian Information Centre for International Credentials for further information at http://www.cicic.ca/.
Persons are entitled to participate in the appointment process in the official language of their choice.
You must indicate on your application if you require a technical aid for testing or an alternative method of assessment.
Candidates from outside the public service may be required to pay for travel and relocation costs associated with this selection process.
We thank all those who apply. Only those selected for further consideration will be contacted.