Responsibilities
- Conduct high-reaching research in Machine Learning that solves open problems of high practical value and validate it in real-world benchmarks and systems.
- Push the boundaries of knowledge and the state of the art in ML areas including simulation, perception, prediction, and planning for autonomous driving and robotics.
- Partner with a multidisciplinary team including other research scientists and engineers across the ML team, TRI, Toyota, and our university partners.
- Stay up to date on the state-of-the-art in Machine Learning ideas and software.
- Present results in verbal and written communications, internally, at top international venues, and via open source contributions to the community.
- Participate in collaborations with our external research partners (e.g., Stanford, Berkeley, MIT, CMU, UMich).
Qualifications
- Currently pursuing a Ph.D. in Machine Learning, Robotics, Computer Vision, or related fields.
- Experienced in at least one key ML area among Computer Vision, ML theory, AI ethics, or related.
- At least one publication at high-impact conferences/journals (CVPR, ICLR, NeurIPS, CoRL, ICML, RSS, ICRA, ICCV, ECCV, PAMI, IJCV, etc.) on the aforementioned topics or other evidence of pioneering research work (e.g., via open source contributions).
- Some experience in scientific python, Unix, and a common DL framework (preferably PyTorch).
- You can work in collaboration with other researchers and engineers to invent and develop interesting research ideas.
- You are passionate about large scale challenges in ML grounded in physical systems, especially in the space of robotics.
- You are a reliable team-player. You like to think big and have depth. You care about openness and delivering with integrity.
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