- Company Name
- Toyota Research Institute
- Job Title
- Robotics Intern - Large Behavior Models, Learning From Videos (LFV)
- Job Description
-
**Job Title:**
Robotics Intern – Large Behavior Models, Learning From Videos (LFV)
**Role Summary:**
A 12‑week summer research internship focused on advancing robotics through large‑scale vision and language model research. Interns will devise, train, evaluate, and deploy foundation models for robotic perception and decision‑making using multimodal video data, simulators, and real‑world robotics platforms.
**Expectations:**
- Complete a Ph.D. or graduate study in Machine Learning, Robotics, Computer Vision, or closely related field.
- Publish or demonstrate intent to publish in high‑impact conferences (ICLR, NeurIPS, CVPR, ICLR, CoRL, ICRA, etc.).
- Contribute to open‑source projects and present findings at conferences or internal forums.
**Key Responsibilities:**
- Conduct cutting‑edge research solving open problems at the intersection of Computer Vision and Robotics.
- Train and evaluate large‑scale vision models on diverse video datasets, sensors, and multimodal inputs.
- Benchmark model performance on real‑world robotic tasks and simulators.
- Collaborate with interdisciplinary teams (research scientists, engineers, university partners).
- Stay current with state‑of‑the‑art ML and CV techniques and tools.
- Prepare and present research outcomes in written reports, talks, and open‑source releases.
**Required Skills:**
- Advanced programming in Python, Unix shell, and deep‑learning frameworks (PyTorch, TensorFlow).
- Strong foundations in machine learning, computer vision, and robotics concepts (e.g., multi‑view geometry, 3D reconstruction, world modeling).
- Experience with large‑scale model training, data pipelines, and multimodal integration.
- Ability to analyze, benchmark, and interpret model results against robotic performance metrics.
- Excellent communication skills for writing papers, reports, and giving presentations.
**Required Education & Certifications:**
- Current Ph.D. candidate (or equivalent) in Machine Learning, Robotics, Computer Vision, or a related discipline.
- Optional certifications in relevant ML/DL tools or robotics are welcomed but not mandatory.
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