Skip to content

Researcher - Machine learning and Perceptual Quality

    • Edmonton, Alberta
  • gubdr

Job description

Huawei Canada has an immediate 12-month contract opening for a Researcher.


About the team:

The Software-Hardware System Optimization Lab continuously improves the power efficiency and performance of smartphone products through software-hardware systems optimization utilization of AI throughout difference components. We keep tracking the trends of cutting-edge technologies, building the competitive strength of mobile AI, competitive camera Perceptual quality, graphics, multimedia, and software architecture for mobile phone products.


About the job:

  • Research and implement algorithms to improve image quality for camera products: Focus on developing and optimizing deep learning-based algorithms to enhance image quality.
  • Research on algorithms to improve image quality for camera products. Using optimization, deep learning, fine-tuning (e.g. LoRA), Image quality assessment, reinforcement learning, etc.
  • Conduct research on foundation models (CLIP-LMMs and LLMs) and diffusion models with specialized application on image quality assessment (IQA) and image style transfer.
  • Large language model soft prompting techniques for specializing in image quality assessment question answering.
  • Research in the field of color style transfer, AI white balancing and Tone mapping.
  • Research, design and develop deep learning tools, metrics and workflows to improve camera perceptual quality.
  • Keeping up-to-date on recent advances in related fields and publish in top tier conferences.

Job requirements

What you'll bring to the team:

  • Ph.D. or MSc. in computer science, computer engineering or related fields.
  • Solid knowledge in general machine learning and AI.
  • Good understanding about statistics, EDA and OpenCV library.
  • Strong coding abilities using Python, Github, Linux shell scripting, etc.
  • Excellent communication skills, self-motivated, with creative thinking and attention to details.
  • Solid knowledge about foundation models, diffusion models, and prompt learning.
  • Familiarity with LLM fine-tuning techniques and computation photography such as knowledge about color coordinates, tone mapping and white balancing is a bonus.
  • Solid research experience as demonstrated by publications.

or