Flawless is hiring a
Research Scientist Intern

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Flawless

πŸ’΅ ~$48k-$75k
πŸ“Internship - United Kingdom

Summary

Join a close-knit team at Flawless as a research scientist intern on the neural rendering team to work on cutting-edge AI projects and contribute to shaping the future of filmmaking.

Requirements

  • On-going Ph.D. in Visual Computing, Computer Vision, Machine Learning, or a related field
  • Proven track record of first-authored publications at leading conferences (e.g., SIGGRAPH, CVPR, ECCV, ICCV, NeurIPS, ICLR, ICML) or journals (e.g., PAMI, IJCV, JMLR, ToG)
  • 2+ years experience with building systems based on Computer Graphics, Computer Vision, or Machine Learning methods
  • Strong experience with deep learning and computer vision in one or more of the following fields
  • Generative Neural Networks (Diffusion Models, GAN, VAE, etc. )
  • Neural networks and transfer learning
  • Un-supervised or self-supervised learning
  • Few/zero-shot learning for image synthesis
  • Neural talking head synthesis
  • Domain adaptation techniques for image face synthesis
  • 3D computer vision
  • Proficiency with deep learning frameworks such as PyTorch
  • Proficiency in statistical methods and numerical optimization
  • Interest in building real-world tools with product impact

Responsibilities

  • Participating in cutting-edge research in 3D-controlled dynamic face neural rendering
  • Solving real problems in enabling audio-driven photorealistic talking head synthesis
  • Developing efficient deep neural network models for photorealistic neural rendering
  • Collaborating with and supporting other researchers across various departments
  • Pushing the state-of-the-art research from top-tier conferences (e.g. CVPR, ICCV, ECCV, SIGGRAPH, etc.)

Preferred Qualifications

  • Experience with 3DMM and statistical face models
  • Experience with Transformer, CNN, GAN, and Diffusion model architectures
  • Experience with differentiable rendering pipelines, such as PyTorch3D

Benefits

  • Autonomy
  • A hybrid working environment

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