In XRCIA, we aspire to achieve a vision of social presence in VR and AR where people are enabled to interact with each other across distances in a way that is indistinguishable from in-person interactions. We are looking for exceptional researchers who are excited about designing and implementing models that transform partial human information into realistic VR representations.
Requirements
- First author publications in computer vision, machine learning or computer graphics peer-reviewed conferences (e.g. CVPR, ECCV, ICCV, NeurIPS, ICLR, or SIGGRAPH, etc.)
- Experience with realistic 3D geometry/apperance estimation/generation or motion modeling
- Experience with generative models such as Diffusion Models, GANs or VAEs for image and geometry generation.
- 3+ years of experience with prototyping algorithms in Python.
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
- Experience with Neural Radiance Fields, Visual Transformers or Large Language Models.
Responsibilities
- Develop state-of-the-art algorithms and models that can transform information deficient inputs (e.g. cameras with limited visibility, pose, text, audio) into indistinguishable-from-reality VR representations (e.g. faces, bodies, hair, clothes, motion)
- Collaborate with other teams to push the research that enables mid to long-term products
- Publish research results in top-tier journals and at leading international conferences
Other
- 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
- Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
- Proven track record of achieving significant research results as demonstrated by grants, fellowships and/or patents.
