Reference Number
DOE19J-020038-000187
Selection Process Number
19-DOE-ONT-EA-350879
Organization
Environment and Climate Change Canada
Year
2019-2020
Days Open
14
Classification
City
MULTIPLE
Type
External
Total
17
Employment Equity
9
(52.9%)
Screened out
15
(88.2%)
Screened in
0
(0%)
Employment Equity 52.9% 9
Screened Out 88.2% 15
Screened In 0% 0
Women 0% 0
Visible minority 35.3% 6
Indigenous 0% 0
People with disabilities 0% 0
English 52.9% 9
French 47.1% 8
Citizens 47.1% 8
Permanent Residents 0% 0
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The graduate student will work on the development of scientific analysis codes to analyze the 1+ year dataset collected from a new Far Infrared Radiometer (FIRR) instrument installed in the Arctic. Specifically:
1. Begin the design of a cloud retrieval model using the optimal estimation method.
2. Begin development of a neural network to retrieve a water vapour column or vertical profile from the FIRR observations in support of numerical weather forecast systems for water vapour measurements.
3. Test different filter combinations using a Forward Model (as a virtual FIRR) and quantify their added value.
4. Determine the optimal averaging time for each filter by determining the minimum signal-to-noise ratio required for each filter.
The graduate student will work as part of a larger research team in an office environment. The primary office location is the Environment and Climate Change Canada (ECCC) office in Dorval (outside of Montreal). Frequent (at least once a month) travel to the ECCC office in Downsview (Toronto) is also required. Both offices are research environments focusing on numerical weather prediction forecast modeling, cloud physics, and Arctic meteorology using high-performance computing. The student must be able to work independently on their research project as well as part of a larger team.
Positions to be filled: 1
Your résumé.
Contact information for 1 references.
EDUCATION
ED1. The student must be currently enrolled in a Master's or Doctoral’s Program in a recognized post-secondary academic institution as a full-time student in one of the following specializations: Physics / Computer Science.
Background knowledge in physics is required to understand the FIRR’s technical operation, scientific dataset, and interpret results. Knowledge in computer science is required in order to be able to develop software codes from scratch capable of reading data files, analyzing them, and producing products such as plots and statistical analyses using the FIRR’s dataset.
EXPERIENCE:
EX1. Experience with atmospheric observations of the Arctic.
Bilingual - Imperative (BBB/BBB)
Information on language requirements
K1. Knowledge of atmospheric physics, radiative transfer, and optics.
K2. Knowledge of the optimal estimation method and cloud retrieval models.
A1. Ability to analyze large scientific datasets from multiple instruments of various formats.
A2. Ability to develop complex neural network models and retrieval algorithms.
A3. Ability to present scientific results both orally and in the form of scientific publications.
Organizational needs:
Must be willing and able to travel to and from the ECCC office in Toronto (Downsview) at least once a month. Must be willing and able to work independently and as part of a larger team. Must present results to colleagues and provide status reports on an ongoing basis.
Reliability Status security clearance
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 will be given to Canadian citizens.
We thank all those who apply. Only those selected for further consideration will be contacted.