Research Scientist, Generative Avatars (PhD)

The Generative Avatars group at Codec Avatars organization is building social presence in VR and AR where people can interact with each other across distances in a way that is indistinguishable from in-person interactions. We are seeking researchers who are interested in designing and implementing next generation digital human representations with large-scale training.Research Scientist, Generative Avatars (PhD) Responsibilities

• Develop and apply state-of-the-art generative models, such as Diffusion Models, GANs, and VAEs, to build foundational human models for codec avatars.
• Design and run large-scale experiments to evaluate the performance of generative models on various tasks, including:
  1. Image/video generation: generating high-quality images and videos
  2. Multi-view generation: generating 3D consistent and coherent images and 3D content.
• Collaborate with other teams to integrate generative models into the codec avatar pipeline and push the research that enables mid- to long-term products.
• Publish research results in top-tier journals and at leading international conferences.

Minimum Qualifications

• Currently has or is in the process of obtaining a PhD degree and/or postdoctoral assignment in the field of computer vision, computer graphics, machine learning, or a related field
• First-author publications in computer vision, machine learning, or computer graphics peer-reviewed conferences (CVPR, ECCV, ICCV, NeurIPS, ICLR, or SIGGRAPH, etc.)
• Experience with generative models, such as Diffusion Models, GANs, or VAEs, and/or Vision Transformers

Preferred Qualifications

• Proven track record of achieving significant research results as demonstrated by grants, fellowships, and/or patents
• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open-source repositories (e.g., GitHub)
• 3+ years of experience with prototyping algorithms in Python
• Experience in implementation of large-scale training: parallelisms, sharding strategies, custom kernels.
• Experience with large-scale experiment design and execution.
• Familiarity with the avatars pipeline and/or experience working with human-centric data

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