Develop and train foundation models for robotics, align text-based reasoning with low-level control policies, design zero-shot generalization experiments, integrate models into robotic systems with interdisciplinary teams, and present research findings.
We are seeking an innovative and experienced Embodied AI Researcher, focusing on the development and application of foundation models in robotics. The successful candidate will contribute to cutting-edge research, designing models and experiments that advance the field of robotics through deep learning and zero-shot generalization.
Responsibilities:
- Train foundation models for robotics, utilizing architectures similar to RT-X.
- Align text-based reasoning processes with low-level robotic control policies.
- Design and conduct experiments to evaluate zero-shot generalization in robotic systems.
- Collaborate with interdisciplinary teams to integrate AI models into practical robotic applications.
- Document and present research findings at internal and external conferences.
Qualifications:
- PhD or equivalent research experience in Deep Learning and Robotics.
- Proven track record of publications in top-tier conferences such as CoRL, ICRA, and NeurIPS.
- Practical experience with imitation learning and behavior cloning techniques.
- Strong programming skills in Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
- Excellent problem-solving skills and the ability to work independently and as part of a team.
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