CV0224: Internship - Language-Guided Human-Robot Interaction
About The Position
MERL is looking for a self-motivated intern to research on the topic of language-guided dynamic human-robot interaction in simulations. The intern must have a strong background in state-of-the-art machine learning research including the knowledge of agentic AI technologies, toolboxes to train/fine-tune large vision-and-language models, as well as expertise working on simulation platforms such as AI Habitat or similar. The intern is expected to collaborate with researchers in the computer vision team at MERL to develop algorithms and prepare manuscripts for scientific publications.
Requirements
- Experience in realistic simulators, including AI Habitat, TDW, etc.
- Experience in modeling agentic pipelines for solving complex tasks, including assimilating multimodal data, natural language interaction, and physical reasoning.
- Strong computer vision and machine learning foundations, including reinforcement learning, training large vision-and-language models, etc.
- Strong track record of publications in top-tier computer vision and machine learning venues (such as CVPR, NeurIPS, etc.)
- Must be enrolled in a graduate program, ideally towards a Ph.D.
Responsibilities
- develop algorithms
- prepare manuscripts for scientific publications
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What This Job Offers
Career Level
Intern
Education Level
Ph.D. or professional degree
Number of Employees
5,001-10,000 employees
