MERL is seeking highly motivated interns for research positions in guidance, navigation, and control of spacecraft. The ideal candidates have experience in one or more of the following topics: astrodynamics, the three-body problem, relative motion dynamics, rendezvous, attitude control, orbit control, orbit determination, nonlinear estimation, and optimization-based control. PhD students in aerospace, mechanical, or electrical engineering are encouraged to apply. Publication of results produced during the internship is expected. The duration of the internships are 3-6 months, and the start dates are flexible.

MERL is seeking a highly motivated, qualified individual to join our internship program in the summer of 2022. The ideal candidate will be a senior Ph.D. student specializing in computer science, aerospace, mechanical, or applied mathematics. Research experience in computational fluid dynamics (CFD), C++ (OpenFOAM level), and Python (Keras w/ TensorFlow, PyTorch, etc.) is very desirable. Solid background in two or more of the following areas is required: Physics-Informed Neural Nets (PINNs), adjoint analysis, PDE-constrained optimization, reduced-order modeling (ROMs), statistical learning, parameter estimators, regression techniques, and probability theory. The starting date is flexible, and the internship will last 3-4 months.

MERL is seeking a highly motivated and qualified intern to collaborate with the Control for Autonomy team in research on planning and control for autonomous vehicles. The research domain includes algorithms for path planning, vehicle control, high level decision making, sensor-based navigation, driver-vehicle interaction. The ideal candidate is expected to be working towards a PhD with strong emphasis in vehicle guidance and control, and to have interest and background in as many as possible of: vehicle dynamics modeling and control, predictive control algorithms linear and nonlinear systems, motion planning, convex, non-convex, and mixed -integer optimization, statistical estimation, cooperative control. Good programming skills in MATLAB, Python or C/C++ are required, knowledge of rapid prototyping systems, automatic code generation or ROS is a plus. The expected start of of the internship is in the late Spring/Early Summer 2022, for a duration of 3-6 months.