Reference Number
RSN23J-013750-000428
Selection Process Number
2023-RSN-RAP-EETS-578749
Organization
Natural Resources Canada
Year
2023-2024
Days Open
3
Classification
City
MULTIPLE
Type
External
Total
11
Employment Equity
5
(45.5%)
Screened out
9
(81.8%)
Screened in
0
(0%)
Employment Equity 45.5% 5
Screened Out 81.8% 9
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 63.6% 7
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.
NRCan seeks an undergraduate or graduate student for summer of 2023 hire in the space of artificial intelligence, natural language processing and data analysis for materials science. The project focuses on developing or utilizing AI algorithms to perform automated data conversion of materials science data. The successful applicant will be responsible for data preparation, coding and working with researchers to develop algorithms for data loading and conversion.
Positions to be filled: 1
Your résumé.
A covering letter "Please provide a CV, an up to date copy of your transcripts, and provide 2 professional references."
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
To be considered for RAP opportunities, students must be:
1. Students enrolled or able to enroll in a program at University of Toronto (proof will be required before the start date) with specialization in Materials Science and Engineering.
2. Have demonstrated through experience, or work product, a capability to apply machine learning/artificial intelligence techniques to materials science data; and
3. The minimum age to work in the province or territory where the job is
located;
English essential
Information on language requirements
1.) Competence in programming with Python, R, or Julia languages.
2.) Experience using repositories to organize and version control scientific code
3.) Experience in organizing, loading and working with disparate datasets.
In support of achieving a diverse and inclusive workforce, selection is to candidates who self-declare as a member of the Employment Equity group: women.
Reliability Status security clearance - Reliability Status security clearance - This factor is not used at the screening stage. The hiring department is responsible for the security clearance process.
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 those who apply. Only those selected for further consideration will be contacted.