Overview
MERL is seeking a highly motivated candidate to collaborate in the development of decision making, planning and control for teams of ground robots in tasks 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 are expected to be published in top-tier conferences and/or journals. The position will take place during Fall/Winter 2025 (exact dates are flexible) with an expected duration of 3-6 months.
Qualifications and 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:
o Formal methods and set based methods (temporal logics, reachability, invariance)
o Model predictive control (design, analysis, solvers)
o Reinforcement learning for planning
o Cooperative planning and control for multi-agent systems
o Programming in Python or Matlab or Julia
Additional Useful Experience
* 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
How to Apply
Please use your cover letter to explain how you meet the requirements above, preferably with links to papers, code repositories, etc., indicating your proficiency.
Equal Opportunity and Employment Information
MERL provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, religion, sex, or genetics. In addition to federal law requirements, MERL complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
MERL expressly prohibits any form of workplace harassment based on race, religion, sex, or expression, genetic information, veteran status, or other protected characteristics. Improper interference with the ability of MERL’s employees to perform their job duties may result in discipline up to and including discharge.
Working at MERL requires full authorization to work in the U.S. and access to technology, software and other information that is subject to governmental access control restrictions. Employment is conditioned on continued full authorization to work in the U.S. and the availability of government authorization for the release of these items, which might include obtaining an export license or other documentation. MERL may delay commencement of employment, rescind an offer of employment, terminate employment, and/or modify job responsibilities, compensation, benefits, and/or access to MERL facilities and information systems, as MERL deems appropriate, to ensure practical compliance with applicable employment law and government access control restrictions.
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