Internship: High-Dimensional Reinforcement Learning
MERL is looking for a highly motivated intern to work on developing reinforcement learning algorithms to solve problems with high-dimensional state and action spaces. Successful candidate will collaborate with MERL researchers to design, analyze, and implement new algorithms, conduct experiments, and prepare results for publication. The candidate should have a strong background in reinforcement learning and machine learning/statistics. The candidate should be comfortable implementing the developed algorithms in Python. Prior exposure to deep learning and hands-on experience with packages such as Keras, TensorFlow, or Theano is a plus. The candidate is expected to be a PhD student in Computer Science, Electrical Engineering, Operations Research, Statistics, Applied Mathematics, or a related field, with relevant publication record. The starting date is flexible and can be as early as April 2017.
Research Area: Data Analytics
Contact: Amir-massoud Farahmand
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