Research Intern — Human Pose Understanding and Vision-Language Models

We are looking for a research intern to join us for a research project aimed at publication at a top-tier venue. The intern will design and develop novel systems that explore the interaction between human pose understanding and vision-language models (VLMs), advancing how these modalities can be combined to reason about human motion, activity, and embodied behavior across images and video.

Description

Our group develops hand and body pose tracking algorithms for various apple devices and applications. One such example includes the hand tracking input for the Vision Pro.

Minimum Qualifications

Currently enrolled in a graduate program (M.Sc. or Ph.D.) in Computer Science, Electrical Engineering, or a related field
Publications at top-tier venues (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, EMNLP or similar)
Strong programming skills in Python and experience with deep learning frameworks (e.g., PyTorch)
Solid foundation in computer vision, natural language processing, or multimodal learning

Preferred Qualifications

Demonstrated expertise working with Vision-Language Models (VLMs) and/or Large Language Models (LLMs)
Experience with human pose estimation, motion modeling, or related body-tracking tasks
Familiarity with video understanding tasks and temporal modeling
Familiarity with multimodal learning and benchmarks that combine language with visual or spatial data
Experience with prompt engineering and optimization techniques