CO-OP Student (Control & Autonomous Systems Engineering, 07-76) (January-June 2025)

Group 76 - Control & Autonomous Systems Engineering - Summer Research Program Intern (CO-OP)

At MIT Lincoln Laboratory, located at the vibrant nexus of academia, industry, and government, we are renowned for our groundbreaking solutions to some of the nation’s most intricate and complex challenges. Within the Engineering Division, our team collaborates extensively—not only within the Laboratory but also across the MIT campus—bridging a myriad of disciplines to innovate through robust analysis, design, prototyping, and testing.

Our team culture is energized by our diverse group of talented professionals who bring a rich mix of skills and experiences to the table. We champion a balanced approach to work and life, promoting productivity through flexible schedules and hybrid work arrangements.

The Control and Autonomous Systems Engineering Group at MIT Lincoln Laboratory is at the forefront of research and development in autonomy. Our projects range from theoretical research to the actual deployment of systems in oceanic, terrestrial, aerial, and space environments. We are looking for innovative thinkers who are eager to drive advancements in autonomous systems and robotics. If you are ready to contribute to cutting-edge research and development within a multidisciplinary team, MIT Lincoln Laboratory offers a dynamic and supportive environment for you to thrive.

Job Description

Under the direction of MIT Lincoln Laboratory technical staff , the summer intern will participate in various aspects of autonomous systems development, including the design, development, and test of software algorithms and hardware prototypes. Projects may include pointing and stabilization of space optical payloads, small satellite state estimation and control, precision navigation of autonomous aerial, ground, and underwater vehicles, coordination of teams of heterogeneous unmanned systems, and basic research pursuing efficient human-robot interaction and teaming.

Requirements

The successful candidate will be pursuing an undergraduate or graduate degree in a relevant field such as Electrical, Mechanical or Robotics Engineering or Physics, Computer Science, or Applied Mathematics. Course work or hands-on research experience with controls, robotics, computer vision and/or machine learning is a desired.