Research Scientist Intern, Neural Rendering, Digital Avatars (PhD)

Description du poste:

The Reality Labs Research (RL-R) Team in Zurich, CH is looking for research interns to tackle the most ambitious problems in the creation of digital avatars. In this internship, we aim to build a neural renderer that delivers high-quality avatar appearance under a wide range of body motions and face expressions. We plan to leverage pre-trained generative models with additional controls over body pose, face expressions and hair motion, and work towards generation of 4D-consistent avatars. We envision a world where people connect across vast distances so our roles focus on generation and modeling avatars with a highly detailed appearance. As part of our team you will explore new ways of generating controllable avatars and will be able to leverage high-quality captures and/or synthetic data to go beyond existing state-of-the-art approaches. Our internships are sixteen (16) to twenty four (24) weeks long and we have various start dates throughout the year. Research Topics: *Virtual characters, animatable avatar creation *Controllable video generation *Real-time neural rendering

Research Scientist Intern, Neural Rendering, Digital Avatars (PhD) Responsibilities

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Develop novel algorithms in areas such as controllable avatar generation, and temporally- and view-consistent neural rendering.

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Collaboration with and support of other researchers across various disciplines.

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Communication of research agenda, progress and results.

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If successful, write up results for possible publication.

Minimum Qualifications

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Currently has, or is in the process of obtaining, a PhD in the field of Computer Science, Computer Vision, Machine Learning or related field

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Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment

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Understanding of computer vision/graphics, 3D geometry, neural rendering, human modeling

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Experience with deep learning frameworks like PyTorch

Preferred Qualifications

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Knowledge of state-of-the-art human face and body representations

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Experience with fine-tuning of generative models

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Intent to return to degree-program after the completion of the internship

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Proven track record of achieving significant results as demonstrated by publications at leading conferences such as CVPR, ECCV/ICCV, NeurIPS, SIGGRAPH, or similar