2024 Call for Interns, Creative Vision

The Creative Vision Team at Snap Research seeks highly motivated PhD students in Computer Vision for 16-24 week internships in multiple locations in multiple locations.

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At Creative Vision, we build an artificial creative mind and bring it into every device, unlocking and enhancing the creativity of our users and creators. Over the last 5 years our team has published 60+ of top conference papers–20 in 2022 and 23 in 2023. This led to 20+ impactful features developed and shipped into Snap products. The team organized highly attended tutorials based on our work: CVPR'21 Tutorial on Creativity, ECCV'22 Tutorial on Video Synthesis, CVPR’23 Tutorial on Efficient Neural Networks. We have a robust internship and collaboration program, which in the past 5 years consisted of 60+ interns and collaborations with 20+ academic labs.

In 2024, we’ll focus on large-scale foundation projects in these areas:

  • Foundational models for Image, Video, 3D and 4D synthesis and editing: We build the best text-to-X models for Snap’s unique use-cases.
  • Efficient AI: We focus on optimizing on-device and server-side latency for 2D, 3D foundational models.
  • Personalized Generative AI: We personalize foundational models to your images and preferences, such that the generated outputs are tailored for your taste!
  • Multimodal Generative AI: We combine multiple modalities for simple and powerful generation and editing.

If these topics sound exciting for you, join us for the spring, summer or fall in 2024. You’ll work towards a publication at a top conference with a possibility to impact Snap products and millions of Snapchatters!

Please email the team directly (preffered) or submit your application and select the Creative Vision team.

Team

Hsin-Ying Lee

Image, video, 3D, 4D synthesis and manipulation

Jian Ren

Foundational text-to-image models & Efficient AI for 2D and 3D

Junli Cao

Neural rendering, 3D Generation, On-device 2D & 3D

Yuwei Fang

Multimodal Learning, generation, editing, personalization

Peiye Zhuang

Image, video, 3D & 4D generation and editing

Sergey Tulyakov

2D and 3D image and video synthesis & animation

Aliaksandr Siarohin

Video generation

Anil Kag

Foundational text-to-image models, Efficient AI

Ivan Skorokhodov

Image, video and 3D generative models

Chaoyang Wang

3D & 4D reconstruction and synthesis

Kfir Aberman

Generative AI, Personalization

Qing Jin

Efficient AI, Generative AI

Jackson (Kuan-Chieh) Wang

Generative AI, Personalization