Job title: Machine Learning Engineer, Research Officer
Company: National Research Council Canada
Job description: Priority may be given to the following designated employment equity groups: women, Indigenous peoples* (First Nations, Inuit and Métis), persons with disabilities and racialized persons*.
- The Employment Equity Act, which is under review, uses the terminology Aboriginal peoples and visible minorities.
Candidates are asked to self-declare when applying to this hiring process.
City: Ottawa
Organizational Unit: Ocean, Coastal and River Engineering
Classification: RO
Tenure: Term to January 7, 2028
Language Requirements: English
Note: Due to the nature of the work and operational requirements, this position will require some physical presence at the NRC work location identified, however, the option of a hybrid work arrangement (a combination of working onsite and offsite), may be possible.
Your Challenge
Great Minds. One Goal. Canada’s Success.
Help bring research to life and drive your career forward with the National Research Council of Canada (NRC), Canada’s largest research and technology organization.
We are looking for an organized and dynamic Machine Learning Scientists, to support the Ocean, Coastal and River Engineering Research Centre at its Ottawa location. The selected candidate would be someone who shares our core values Integrity, Excellence, Respect and Creativity.
NRC’s GOCF Research Centre supports a broad cross-section of industry sectors by developing creative and practical solutions to applied engineering challenges in rivers, coastal, ships and marine environments. We provide expertise and tools to identify, adapt, and integrate advanced solutions into systems that improve the performance and safety of ocean, coastal, shipping and marine operations, management and effective utilization of inland water resources, address the challenges of climate change, and protect infrastructure, property and people from risks of severe weather and climate events. Using numerical modelling tools, machine learning, field investigations, and world-class model test facilities (including two ice tanks – of which one is the longest in the world – five wave basins and three flumes), we are creating safe, efficient and sustainable solutions to engineering challenges.
GOCF has a strategy that revolves around using data science & AI in all aspects of its research. We are looking for a passionate data scientist / machine learning expert with appropriate domain expertise, who can apply the latest research and algorithms to help solve our problems and produce novel, high-quality research. As a member of the “Data Science & AI” team, you will use and evaluate machine learning models using a variety of large data sets (e.g., in-situ environmental conditions, satellite imagery, ship data, model scale data, numerical data), state-of-the-art computing facilities (multi-GPUs), and cloud services, to apply to various projects that are strategic to GOCF, including (but not limited to) coastal monitoring, ship performance, target detection from underwater cameras and remote sensing, autonomous ships, weather routing, human factors, and many others.
The primary responsibility of the Machine Learning Engineer will be to advance and maximize the impact of GOCF Research Centre’s research nationally and internationally through developing new models, technologies, advanced data analysis techniques, and decision support tools. As a subject matter expert, the Machine Learning Engineer will work on a variety of multidisciplinary projects to leverage the latest state-of-the-arts computer vision, machine learning and data analytics methods to support our Research Centre’s R&D objectives.
The Machine Learning Engineer is also expected to actively participate in the development of project proposals, execute project management plans, disseminate research outcomes and deliver superior technical services. Additionally, there will also be opportunities to explore independent research interests, participate in postdoctoral mentoring and development programs, and access ideation funds offered by the NRC.
Screening Criteria
Applicants must demonstrate within the content of their application that they meet the following screening criteria in order to be given further consideration as candidates:
Education
Master’s degree with relevant research experience or Ph.D. . in a discipline of engineering such as Civil, Computer, Environmental, or Water Resources/Hydrologic Engineering, or in Ocean and Naval Architecture, Computer Science, Machine Learning, Statistics, or a related quantitative field.
The ideal candidate would possess the skills required to determine and use the appropriate machine learning and data analytical methods specific to the problems at hand, and would also possess domain expertise relevant to NRC-OCRE.
For information on certificates and diplomas issued abroad, please see
Experience
- Significant* Experience using current state-of-the art in machine learning, including DNNs, CNNs, RNNs, and other frequently used methods in the field of computer vision, classification, regression and predictive modelling.
- Significant* experience with statistical modelling and analysis of large imagery, geospatial and time series datasets originating from instrumental records, time-lapse cameras, optical and radar satellite sensors, regional and global climate modelling experiments or re-analyses products using both conventional and modern machine learning approaches/frameworks.
- Significant* experience using Python, virtual environments and data science packages (e.g. numpy, scipy, pandas, xarray, dash) to read, manipulate and analyse large temporal and spatial datasets.
- Demonstrated experience in using computer vision and machine learning methods in one or more areas of OCRE research such as coastal engineering, water resources, ice or naval architecture would be considered an important asset.
- Demonstrated experience developing and deploying online analytical tools, dashboards and decision support systems would be considered an important asset.
- Demonstrated experience in the full spectrum of research activities including identification of research requirements, proposal writing, project management, client/stakeholder interaction, data production and analysis, and reporting through written documentation, presentations and publishing would be considered an important asset.
*Significant refers to at least three (3) years of experience.
Condition of Employment
Secret (II)
Language Requirements
English
Assessment Criteria
Candidates will be assessed on the basis of the following criteria:
Technical Competencies
- Significant* ability and knowledge to use current state-of-the art machine learning libraries, such as TensorFlow or PyTorch, to apply various methods, such as DNNs, CNNs, RNNs and other, in the field of computer vision, classification, regression and predictive modelling.
- Significant* ability to develop statistical models and analyze large optical and radar imagery, geospatial and time series datasets originating from instrumental records, time-lapse cameras, satellite sensors, regional and global climate modelling experiments or re-analyses products using both conventional and modern machine learning approaches/frameworks.
- Significant* ability to use Python, virtual environments and data science packages (e.g. numpy, scipy, pandas, xarray, dash) to read, manipulate, visualize and analyse large temporal and spatial datasets.
- Knowledge of GIS software for processing, analyzing and understanding geospatial data; and visualization and graphical software tools for producing high quality graphics, maps, and animations would be considered an important asset.
- Demonstrated ability in using computer vision and machine learning methods in one or more areas of OCRE research such as coastal engineering, water resources, ice or naval architecture would be considered an important asset.
- Demonstrated ability to develop and deploy online analytical tools, dashboards and decision support systems would be considered an important asset.
Behavioural Competencies
- Research – Continuous professional learning (Level 2)
- Research – Results orientation (Level 2)
- Research – Initiative (Level 2)
- Research – Teamwork (Level 2)
- Research – Self-knowing and self-development (Level 2)
- Research – Creative thinking (Level 3)
Competency Profile(s)
For this position, the NRC will evaluate candidates using the following competency profiles:
Compensation
This position is classified as a Research Officer (RO), a group that is unique to the NRC. Candidates are remunerated based on their expertise, outcomes and impacts of their previous work experience relative to the requirements of the level. The salary scale for this group is vast, from $57,220 to $161,754 per annum, which permits for employees of all levels from new graduates to world renowned experts to be fairly compensated for their contributions.
NRC employees enjoy a wide-range of including comprehensive health and dental plans, vacation, sick, and other leave entitlements, disability insurance and pension plans.
The NRC Advantage
The National Research Council of Canada (NRC) is the Government of Canada’s largest research organization supporting industrial innovation, the advancement of knowledge and technology development. We collaborate with over 70 colleges, universities and hospitals annually, work with 800 companies on their projects, and provide advice or funding to over 8000 Small and Medium-sized Enterprises (SMEs) each year.
We bring together the brightest minds to deliver tangible impacts on the lives of Canadians and people around the world. And now, we want to partner with you. Let your expertise and inspirations make an impact by joining the NRC.
At the NRC Employee wellness matters. We offer flexible work schedules as well as part-time work to help employees maintain work-life balance. We are one of the few federal organizations that close our offices during the December holiday season. We offer professional learning and development opportunities such as conferences, workshops, and a suite of mentorship, award and recognition programs. Diversity enables creativity and innovation. Fostering a diverse, inclusive, welcoming and supportive workplace is important to us, and contributes to a more inclusive Canadian innovation system. We welcome all qualified applicants and encourage you to complete the employment equity self-declaration questions during the job application process. Please let us know of any accommodation measures required to help you to be assessed in a fair and equitable manner. Please note that the information you provide will be treated confidentially.
Help us solve problems for Canada. Grow your career with us today!
Notes
- Relocation assistance will be determined in accordance with the NRC’s directives.
- A pre-qualified list may be established for similar positions for a one year period.
- Preference will be given to Canadian Citizens and Permanent Residents of Canada. Please include citizenship information in your application.
- The incumbent must adhere to safe workplace practices at all times.
- We thank all those who apply, however only those selected for further consideration will be contacted.
Please direct your questions, with the requisition number (20900) to:
E-mail:
: 506-686-2961
Closing Date: 15 January 2024 – 23:59 Atlantic Time
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*If you are currently a term or continuing employee at NRC, please apply through the SuccessFactors Careers module from your NRC computer.
Date modified: This page is updated continuously.
Expected salary: $57220 – 161754 per year
Location: Ottawa, ON
Job date: Fri, 22 Dec 2023 23:15:03 GMT
