The Meta Reality Labs Research Team brings together a world-class team of researchers, developers, and engineers to create the future of AR and VR, which together will become as universal and essential as smartphones and personal computers are today. The focus of our team is on computer graphics with primary research on the efficient synthesis of high-quality images for AR/VR systems. Our current research areas include custom graphics hardware, rendering algorithms for AR/VR, such as ray casting and machine learning based image synthesis, and differentiable & inverse rendering. For this internship, we are looking for Ph.D. students to investigate various core research problems for physics-based differentiable rendering and inverse rendering, aiming to improve the quality & performance of real object/lighting/scene reconstruction & digitization and enable various high-quality novel AR/VR experiences based on it. Meta Reality Labs offers internships ranging from twelve (12) to sixteen (16), or twenty-four (24) week periods. We encourage submitting papers to high-ranked computer graphics conferences and journals based on the results of the internship.
Research Intern, Neural/Inverse Rendering/Generative 3D Algorithm (PhD) Responsibilities:
- Design and develop novel neural rendering, inverse rendering, or differentiable rendering algorithms to enable and prototype novel AR/VR experiences.
- Deliver the state-of-the-art research outcome to push the boundary of neural & inverse rendering research.
- Collaboration with and support of other researchers and engineers from various disciplines.
- Communication of research agenda, progress and results.
- Currently has, or is in the process of obtaining, a PhD degree in the field of Computer Graphics, Computer Vision, Machine Learning or related field.
- 3+ years of experience in C/C++, python or ML programming.
- Familiar with at least one popular deep learning framework, such as PyTorch and Tensorflow.
- Basic knowledge on image formation model and graphics rendering pipeline.
- Deep understanding and hands-on experiences in one or more of the following: neural rendering / inverse rendering / differentiable rendering / physics-based real-time or offline rendering / physically based materials and lighting / ML-based graphics rendering related research.
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
- Experience in cutting-edge research in neural rendering, inverse rendering, physics-based differentiable rendering, 3D object/scene reconstruction, photorealistic lighting/material estimation, texture/image compression.
- 1+ years of experience in working on neural/inverse rendering and the related applications.
- Experience in modern machine learning methods with hands-on implementation experience.
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as ACM SIGGRAPH/SIGGRAPH Asia, High Performance Graphics (HPG), ACM SIGGRAPH Symposium on Interactive 3D and Graphics (I3D), Eurographics Symposium on Rendering (EGSR), CVPR/ICCV/ECCV, NeurIPS, etc.
- Demonstrated software development experience via an internship, work experience, coding competitions or widely used contributions in open source projects (e.g., Github).
- Interpersonal experience: cross-group and cross-culture collaboration.
- Intent to return to a degree-program after the completion of the internship/co-op.
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
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