2020 Full Scholarship Reinforcement Learning PhD Position in New York University
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Department：Electrical and Computer Engineering, Tandon School of Engineering.
Research area of this position: Design new data-driven learning-based control and decision methods, including but not limited to reinforcement learning.
Number of vacancy: One.
Advisor：Prof. Zhong-Ping Jiang (IEEE Fellow and IFAC Fellow) who has authored or co-authored over 4 books and 200 peer-reviewed journal papers with a G-Scholar h-index of 76. He was named as a Highly Cited Researcher for 2018 by Web of Science. For more details, please see his engineering.nyu.edu.
About the lab: Control and Networks (CAN) Lab is directed by Prof. Zhong-Ping Jiang. The ongoing research programs at CAN Lab involve multidisciplinary studies, from control theory, (deep) reinforcement learning, deep learning, to intelligent transportation systems and biological systems. Novel reinforcement learning algorithms based on robust adaptive dynamic programming have been developed and deployed at CAN Lab for various applications, including autonomous driving and mobile robots.
Qualification: Students with undergraduate or master degrees. Students who major in Applied mathematics, Automation, Control theory, Artificial intelligence or other related areas are preferred.
How to apply: Interested candidates should apply directly and formally to the department, and mention your interest of working with Prof. Zhong-Ping Jiang in your essay. At the same time, please also email your CV and TRANSCRIPTs to both of following addresses: 1point3acres.com; 1point3acres.com; .
Research area of this position: Design new data-driven learning-based control and decision methods, including but not limited to reinforcement learning.
Number of vacancy: One.
Advisor：Prof. Zhong-Ping Jiang (IEEE Fellow and IFAC Fellow) who has authored or co-authored over 4 books and 200 peer-reviewed journal papers with a G-Scholar h-index of 76. He was named as a Highly Cited Researcher for 2018 by Web of Science. For more details, please see his engineering.nyu.edu.
About the lab: Control and Networks (CAN) Lab is directed by Prof. Zhong-Ping Jiang. The ongoing research programs at CAN Lab involve multidisciplinary studies, from control theory, (deep) reinforcement learning, deep learning, to intelligent transportation systems and biological systems. Novel reinforcement learning algorithms based on robust adaptive dynamic programming have been developed and deployed at CAN Lab for various applications, including autonomous driving and mobile robots.
Qualification: Students with undergraduate or master degrees. Students who major in Applied mathematics, Automation, Control theory, Artificial intelligence or other related areas are preferred.
How to apply: Interested candidates should apply directly and formally to the department, and mention your interest of working with Prof. Zhong-Ping Jiang in your essay. At the same time, please also email your CV and TRANSCRIPTs to both of following addresses: 1point3acres.com; 1point3acres.com; .
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