MERL is seeking a highly motivated intern for a research position in spacecraft attitude dynamics and control. The ideal candidate is a PhD student with experience in attitude kinematics and dynamics, multi-body dynamics, Lagrangian or Hamiltonian mechanics, optimization, and control of rigid bodies. Experience in computational fluid dynamics (CFD) using OpenFOAM, multi-phase flow modeling, and volume-of-fluid approach is desirable. Publication of results produced during the internship is expected. The duration of the internship is 3-6 months, and the start date is flexible.

MERL is seeking highly motivated intern to work on the development of novel optimization algorithms. The target applications span a broad range of areas including power systems, control, scheduling, and transportation. Successful candidate will collaborate with MERL researchers to develop and implement new algorithms, conduct experiments, and prepare results for publication. Ideal candidate would be senior PhD student with experience in one or more of the following areas: linear and quadratic programming, active-set methods, and first-order methods for convex programs. Strong programming skills and fluency in C++/Python are expected. Prior experience with popular optimization packages such as Ipopt, Gurobi, Cplex is a plus. The duration of the internship is expected to be 3 months. Start date is flexible. 

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.