This project will explore methods for multi-agent reinforcement learning for a team of aerial robots in dynamic environments. The post-doc will focus on developing learning methods, but will coordinate with other students, post-docs and professors to test the approaches with aerial robots.
For full consideration *please apply by May 25th* Qualifications: PhD in Computer Science or related field Top-tier publications in the general area of multi-agent reinforcement learning (broadly defined) Programming experience in a high-level language such as C++ or python Self-motivated Works well with a team Knowledge of the following is helpful, but not required: deep reinforcement learning, decentralized POMDPs or multi-robot learning. The position will be for up to 2 years and will be supervised by Chris Amato (http://www.ccs.neu.edu/home/camato/) at Northeastern University. Northeastern University is located in the heart of Boston, a city with one of the richest research environments in the world, with over 10K researchers, 50K graduate students, and a top startup community. Northeastern University is home to 35,000 full- and part-time degree students. The past decade has witnessed a dramatic increase in Northeastern’s international reputation for research and innovative educational programs (according to CSRankings.org<http://CSRankings.org>, Northeastern is ranked 19th in the USA overall and 26th in robotics). For more information about Northeastern and the College of Computer and Information Science, please visit http://www.ccis.northeastern.edu/ To apply, please send your CV and either two reference letters or contact information for two references to cam...@ccs.neu.edu<mailto:cam...@ccs.neu.edu> with MARL-postdoc in the subject. Feel free to also email if you want more info. Christopher Amato Assistant Professor College of Computer and Information Science (CCIS) Northeastern University http://www.ccs.neu.edu/home/camato/
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