CA0279: Internship - Heterogeneous multi-agent planning and control
About The Position
MERL is seeking a highly motivated intern to collaborate in the development decision making, planning and control for teams of heterogeneous robots (aerial, ground wheeled, legged etc.) in task such as inspection, monitoring and infrastructure repair. 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 Spring/Summer 2026 (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.
Requirements
- Current enrollment in a PhD program in Mechanical, Electrical, Aerospace Engineering, Computer Science or related programs, with a focus on Robotics and/or Control Systems
- Experience in as many as possible of: Formal methods and set based methods (temporal logics, reachability, invariance) Model predictive control (design, analysis, solvers) Reinforcement learning for planning Cooperative planning and control for multi-agent systems Programming in Python or Matlab or Julia
Nice To Haves
- Knowledge of one or more physics simulators for robotics (e.g., MuJoco)
- Experience with coverage control and pursuit-evasion problems
- Programming in C/C++ or Simulink code generation
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What This Job Offers
Career Level
Intern
Education Level
Ph.D. or professional degree
Number of Employees
5,001-10,000 employees
