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Phd Engineer Jobs in Quebec (NOW HIRING)

CA$105K - CA$122K/yr

PhD in electrical engineering, experimental physics, quantum engineering, systems engineering, or a related field * Relevant experience in quantum technologies, superconducting quantum hardware, or ...

CA$105K - CA$122K/yr

PhD in electrical engineering, experimental physics, quantum engineering, systems engineering, or a related field Relevant experience in quantum technologies, superconducting quantum hardware, or ...

Bachelor's degree in Electrical Engineering or related field (MSEE or PhD preferred) . * Strong understanding of SystemVerilog and mixedsignal verification concepts. * Experience or coursework in ...

You will own key architecture decisions, mentor engineers and researchers, and build high ... Required Qualifications · PhD or MS in Computer Science, Machine Learning, Applied Mathematics ...

PHD in Power Electronics is desirable. * 4+ years of experience as a Project Engineer (Electrical, SCADA, or similar) * Experience with: * BOP design, substations, and WTG integration * CADA systems ...

Master's or PhD in Polymer Science, Materials Science, Chemical Engineering, or a related discipline. * Experience with polymer processing, melt behavior, extrusion, compounding, or thermoforming.

Showing results 21-40

Phd Engineer information

What is a PhD engineer?

A PhD Engineer is an individual who has completed a Doctor of Philosophy (PhD) degree in an engineering discipline. This advanced degree signifies deep expertise in a specialized area of engineering, often involving original research and the completion of a dissertation. PhD Engineers typically work in academia, research and development, or advanced industry roles where they contribute to scientific innovation and technological advancements. Their work often includes conducting research, publishing scholarly articles, and mentoring students or junior engineers.

What are the key skills and qualifications needed to thrive as a PhD engineer?

To thrive as a PhD Engineer, you need advanced expertise in engineering principles, research methodology, and problem-solving, typically supported by a doctoral degree in an engineering discipline. Familiarity with specialized technical tools, modeling software, data analysis platforms, and sometimes professional certifications are commonly required. Exceptional analytical thinking, innovation, and strong communication skills set top PhD Engineers apart in collaborative and research-driven environments. These competencies are vital for driving technological advancements, publishing impactful research, and leading complex engineering projects.

Is a PhD useful in engineering?

A PhD in engineering can be highly valuable for roles involving research, development, and advanced technical problem-solving. It demonstrates expertise, analytical skills, and the ability to conduct independent research, which are often required for specialized or leadership positions in engineering fields.

What jobs can I get with a Phd engineer?

A PhD in engineering qualifies individuals for advanced roles such as research scientist, university professor, R&D engineer, or technical consultant. These positions often require strong analytical skills, expertise in specialized tools or software, and may involve project management or collaboration in innovative environments.

What are the typical career advancement opportunities for a PhD engineer in an industrial setting?

PhD Engineers in industry often start in research and development roles, where they apply their advanced technical expertise to solve complex problems. Over time, they may progress into senior scientist or technical lead positions, and can also transition into management roles such as R&D manager or director. Career growth is often driven by demonstrated innovation, successful project leadership, and strong collaboration skills. Additionally, PhD Engineers frequently have opportunities to shape company strategy, mentor junior engineers, and contribute to patent portfolios.

What is the difference between Phd Engineer vs Research Scientist?

AspectPhd EngineerResearch Scientist
Required CredentialsPhD in Engineering or related fieldPhD in relevant scientific discipline
Work EnvironmentIndustry labs, R&D departments, manufacturingAcademic labs, research institutions, industry R&D
Employer & Industry UsageTech companies, manufacturing firms, engineering firmsUniversities, government agencies, private research firms
Common Search & ComparisonYesYes

Both Phd Engineers and Research Scientists hold doctoral degrees and work in research-intensive environments. Phd Engineers typically focus on applied engineering projects within industry, while Research Scientists often work on fundamental scientific research in academic or government settings. The choice depends on whether you prefer industry application or scientific exploration.

What are popular job titles related to Phd Engineer jobs in Quebec? For Phd Engineer jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Phd Engineer jobs in Quebec look for? The top searched job categories for Phd Engineer jobs in Quebec are:
Infographic showing various Phd Engineer job openings in Quebec as of August 2026, with employment types broken down into 92% Full Time, 3% Part Time, and 5% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.

Computer Vision/ML Engineer

Norbert Health

Montreal, QC • On-site

Full-time

Re-posted 22 days ago


Job description

The company

Norbert is building autonomous robots that deliver healthcare.

Our AI sensing platform mounts on mobile robots and does the work of a care team member-rounding on patients, capturing vitals without contact (FDA-cleared for pulse and respiratory rate, more in the pipeline), running assessments, documenting to the EMR, and escalating when something's wrong. Autonomously.

We're not building demos. We're deployed in real facilities today, monitoring hundreds of patients daily. We're solving one of healthcare's hardest problems: a global nursing shortage that will hit 40% by 2030.

We're a small, international team backed by top-tier VCs, with offices in Brooklyn and Paris. We ship things that matter.

The position

We are looking for our lead deep learning engineer to spearhead the development of our groundbreaking sensing technology.

What you will do:
  • Design, fine-tune, and deploy computer vision models (YOLO, InsightFace, MediaPipe, facial landmark detection, object tracking, pose estimation) for real-time inference on the edge
  • Optimize models for embedded deployment using quantization, pruning, TensorRT, and NVIDIA Triton
  • Build and maintain MLOps pipelines for model training, validation, and performance monitoring
  • Develop video processing pipelines that integrate with both classical signal processing and ML based vital sign extraction
  • Establish engineering best practices and help reduce technical debt as we scale
  • Contribute to the architecture and implementation of the computer vision stack from research to production
What we look for:
  • Master's or PhD degree in Machine learning / Computer vision
  • Strong fundamentals: data structures, CV algorithms, and systems programming
  • Strong C++ skills - this is critical for our edge deployment pipeline
  • Solid Python proficiency for ML experimentation and tooling
  • Ability to work independently, solve complex problems, and drive projects to completion
  • 5+ years experience deploying computer vision models to production, ideally on resource-constrained devices
  • Experience with PyTorch and model optimization for edge AI
  • Proven ability to take models from research to production on embedded hardware

Nice to haves:

  • Experience with NVIDIA Jetson platform, TensorRT, or Triton Inference Server
  • MLOps experience (experiment tracking, model versioning, performance monitoring)
  • Experience with sensor fusion (RGB, IR, depth cameras)
  • Background in medical devices, regulated environments, or healthcare applications
  • Experience working in fast-moving early-stage environments
What we offer:
  • Real impact: your code provides care for patients today
  • High autonomy and technical ownership - you'll shape our computer vision architecture
  • Work at the intersection of cutting-edge AI, edge computing, and healthcare
  • A talented, excellent, diverse and international team
  • Cutting-edge stack: embedded AI, robotics, LLMs, multimodal sensing
  • Talented, international team tackling meaningful problems in remote patient monitoring
  • Competitive salary
  • Transparent, mission-driven culture focused on continuous learning
Employment Type: FULL_TIME