MERL is seeking a highly motivated intern to collaborate in the development decision making, planning and control for teams of ground robot in task such as coverage control, monitoring and pursuit-evasion. The ideal candidate is a PhD student with strong experience in planning and control of multi-agent systems, with background in advanced model-based (e.g., MPC) and learning-based (e.g., RL) methods. The results of the internship are expected to be published in top-tier conferences and/or journals. The internship will take place during Fall/Winter 2025 (exact dates are flexible) with an expected duration of 3-6 months. Please use your cover letter to explain how you meet the following requirements, preferably with links to papers, code repositories, etc., indicating your proficiency.
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Career Level
Intern
Industry
Professional, Scientific, and Technical Services
Education Level
Ph.D. or professional degree
Number of Employees
101-250 employees