- Plan and execute cutting-edge research on developing novel embodied AI algorithms that can learn AR assistance policies in long-tailed and complex interaction tasks prevalent in everyday life.
- Leverage state-of-the-art (SOTA) embodied AI simulators and RL/DRL, neuro-symbolic, AI planning, robotics or stochastic programming methods to train and test policy models.
- Work towards taking on big problems and deliver clear, compelling, and creative solutions to solve them at scale. This is an exciting opportunity to conduct SOTA research while collaborating with other researchers, and engineers to develop, prototype, and test different AI/ML models at-scale for real-world interactive applications.
- Successful internships will also lead to publishable outcomes in top-tier journals or at leading international conferences.
- Currently has, or is in the process of obtaining, a PhD in machine learning, artificial intelligence (AI), robotics, algorithms, computational mathematics or a related fields.
- Proven research skills involving defining problems, exploring solutions, and analyzing and presenting results.
- 2+ years of experience in python and in using machine learning libraries (numpy, scikit-learn, scipy, pandas, matplotlib, tensorflow, pytorch).
- Deep understanding of at least one of the following areas (Transfer/ few-shot/ zero-shot/ continual/ online learning, Self-supervised learning, or Multi- or cross-modal learning, Reinforcement learning, Planning).
- Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
- Interpersonal experience: cross-group and cross-culture collaboration.
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as CVPR, ICCV, ICML, NeurIPS, IJCAI, AAAI, AAMAS, EECV, ICLR, ICRA, IROS, RSS, CoRL etc).
- Experience working and communicating cross functionally in a team environment.
- Intent to return to degree-program after the completion of the internship/co-op.
- Availability for minimum 16 consecutive week internship.
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