Large Behavior Model (LBM) Research Intern, Trustworthy Learning under Uncertainty (TLU)

Responsibilities

• Conduct daring research primarily in Robotics that solves open problems of high practical and/or ethical value and validate it in real-world benchmarks and systems.
• Push the boundaries of knowledge and the state-of-the-art in robotics and LBMs.
• Partner with a multidisciplinary team, including other research scientists and engineers across the TLU team, LBM division, 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 at international conferences, internally, and via open-source contributions to the community.

Qualifications

• Currently pursuing a Ph.D. in Machine Learning, Robotics, or related fields.
• Publication or desire to publish at high-impact conferences/journals (e.g., CoRL, ICLR, NeurIPS, ICML, UAI, AISTATS, TMLR, RSS, ICRA, IROS, RA-L, T-RO, CDC, L4DC, etc.) on some of the aforementioned topics.
• Passionate about large scale challenges in ML grounded in physical systems, especially in the space of robotics.
• Proficiency with one or more coding languages and systems, preferably Python, Unix, and a Deep Learning framework (e.g., PyTorch).
• Ability to work in collaboration with other researchers and engineers of the TLU team to invent and develop interesting research ideas.
• A reliable teammate who loves to think big, go deeper, and strives to deliver with integrity.