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Perception Systems Research Engineer - Surface Transportation

City: Ottawa 

Organizational Unit: Automotive and Surface Transportation 

Classification: RCO 

Tenure: Continuing

Language Requirements: English

 

This position is being re-posted. If you had previously applied, there is no need to re-apply.

Your Challenge

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 a Research Council Officer, Perception Systems Research Engineer, to support the Automotive and Surface Transportation Research Center. The selected candidate would be someone who shares our core values of Integrity, Excellence, Respect and Creativity.


NRC Automotive and Surface Transportation (AST) Research Center has the mandate to advance product and process technologies for producing more fuel-efficient, affordable and environmentally-responsible ground vehicles, and to deliver engineering solutions to complex technology challenges facing today’s surface transportation industries including automotive, heavy and specialized vehicles and rail.

We are seeking a Perception Systems Research Engineer with computer vision and deep learning expertise to join our Intelligent Transportation Systems (ITS) Research Team and help actively push the next stage of perception research at the Surface Transportation industry. This role will focus on developing and integrating new solutions while work alongside researchers and industry clients.

The candidate will design, develop and implemente software, integrate  perception system technologies and hardware (LiDAR, radar,cameras and other sensors) for application in the transportation  sector in the laboratory, on the test track, and for real-world road/rail environments. Focus will be on object detection, recognition, semantic segmentation and sensor fusion from large-scale data sets and multi-sensor/multispectral data. The candidate will also develop and maintain partnerships with researchers from industry, academia and other related government departments to meet the goals of transportation programs at NRC. In addition to a strong technical background, the ideal candidate will have interpersonal and communication skills while working comfortably both independently and in multi disciplinary teams.

The NRC Advantage

Great Minds. One Goal. Canada's Success.

 

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 NRC, we know diversity enables excellence in research and innovation. We are committed to a diverse and representative workforce, an open and inclusive work environment, and contributing to a more inclusive Canadian innovation system. 

 

NRC welcomes all qualified applicants and encourages candidates to self-declare as members of the following designated employment equity groups: women, visible minorities, Aboriginal peoples and persons with disabilities.

 

Please advise of any accommodation measures required to enable you to be assessed in a fair and equitable manner. They are available to all candidates for further assessment. Related information received will be addressed confidentially.

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 or Ph.D. degree in Electrical Engineering, Computer Engineering, Robotics, Mechatronics Engineering, Computer Science or other related field.

Bachelor’s degree with significant relevant industry experience may be considered.

 

For information on certificates and diplomas issued abroad, please see Degree equivalency

Experience

  • Experience in Computer Vision including research, development,  and implementation  of algorithms/codes for object detection, classification and segmentation by LiDAR, Radar, cameras, etc. Experience with other type of sensors is an asset.
  • Experience applying AI, Machine Learning and Computer Vision techniques to manipulate 2D and 3D datasets.
  • Experience in integration and testing of sensing hardware and technologies.


Asset:

  • Experience managing projects and writing research project proposals.
  • Experience with conferences or/and journals publications.

Condition of Employment

Secret (II)

Assessment Criteria

Candidates will be assessed on the basis of the following criteria:

Technical Competencies

  • Programing and hands-on skills in Computer Vision algorithms, and with PCL and OpenCV.
  • Programing skills including debugging, performance analysis and test design in Python C, C++, and/or C#. 
  • Knowledge of machine learning frameworks such as Tensorflow or PyTorch.
  • Knowledge of embedded systems.
  • Knowledge of perception sensors.

Behavioural Competencies

  • Research - Creative thinking (Level 3)
  • Research - Results orientation (Level 2)
  • Research - Teamwork (Level 2)
  • Research - Communication (Level 2)

Competency Profile(s)

For this position, the NRC will evaluate candidates using the following competency profile(s): Research

 

View all competency profiles

Relocation

Relocation assistance will be determined in accordance with the NRC's directives.

Salary Range

This position is classified as a Research Council Officer (RCO), a group that is unique to the NRC. The RCO group uses a person-based classification system instead of the more common duties-based classification system. Candidates are remunerated based on their expertise, skill, outcomes and impacts of their previous work experience. The salary scale for this group is vast, from $56,374 to $159,364 per annum, which permits for employees of all levels from new graduates to world renowned experts to be fairly compensated for their contributions. 

Notes

  • A pre-qualified list may be established for similar positions for a one year period.
  • Candidates must clearly demonstrate in their cover letter how they meet the education and experience factors listed on the poster. Candidates must use the education/experience criteria as a header and then write one or two paragraphs demonstrating how they meet them by providing concrete examples. In addition, the candidate is encouraged to describe in detail when, where and how he/she gained the experience. Failure to provide an appropriate cover letter will result in the rejection of your application. Candidates will not be solicited for incomplete or possible missing information.
  • The successful candidate must be willing to travel ocasionnaly across Canada and internationally to represent NRC.
  • NRC employees enjoy a wide-range of benefits including comprehensive health and dental plans, pension and insurance plans, vacation and other leave entitlements.
  • 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 (11129) to:

E-mail: NRC.NRCHiring-EmbaucheCNRC.CNRC@nrc-cnrc.gc.ca

Telephone: 613-991-2024 

Closing Date: 20 May 2021 - 23:59 Eastern Time

 

 

For more information on career tools and other resources, check out Career tools and resources

 

*If you are currently a term or continuing employee at NRC, please apply through the SuccessFactors Careers module from your NRC computer.

 

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