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We are always looking for qualified candidates who are interested in algorithmic and mathematical development for advancing learning and control of dynamic robotic systems. The work will touch a variety of areas in robotics including vision-based learning, optimal control, reinforcement learning, multi-agent coordination, search and exploration, locomotion, and manipulation.

Candidates will be expected to develop mathematical theory, be well-versed in mathematical proof writing, proficiency in coding languages and environments used in robotics such as C++/C, python, ROS, Linux (Ubuntu) shell scripting, VIM/EMACs, and have excellent speaking and writing proficiencies in English. In addition, candidates will be expected to write journal/conference papers and be able to clearly explain their research and present their work at international conferences.

Research areas include:

• Active learning and optimal control
• Multi-agent search, exploration, and coordination
• Data and Compute efficient learning for distributed complex robotics
• Representations for improving control and learning

Prospective PhD students:

Please email Prof. Ian Abraham email: ian.abraham@yale.edu with a CV, a paragrah as to why you would like to join the lab and a list of relevant publications (if any–optional). For prospective PhD students, please do not forget to apply to the Yale Mechanical Engineering department PhD program and to select Ian Abraham as a potential advisor.