The Control and Dynamical Systems (CD) group at MERL is seeking a highly motivated intern to conduct research on stochastic planning and control for concurrently achieving control performance while concurrently improving the perception of the environment. The ideal candidate is enrolled in a PhD program in Electrical, Mechanical, Aerospace Engineering, Computer Science or related program, with focus on Control Theory. The ideal candidate will have experience in (one or more of) predictive control or model-based motion planning, stochastic control and estimation, interaction between control and estimation algorithms, control with chance constraints, tube-based control. Good programming skills in Matlab (or alternatively Python) are required, working knowledge of C/C++ is a plus. The expected duration of the internship is 3-6 months with flexible start date after April 1st, 2020.

MERL is looking for a self-motivated intern to work on multi-view image processing. The ideal candidate would be a senior Ph.D. student in electrical engineering or computer science with solid research background in image processing such as enhancement, registration, and distortion correction, etc. Experience in sparse modeling is desirable. Proficiency in MATLAB and Python is necessary. The intern is expected to collaborate with MERL researchers to build models, develop algorithms, and prepare manuscripts for scientific publications. The total duration is 3 months.

We are looking for a talented individual to collaborate and facilitate research on new algorithms in mechanism design and distributed auctions. Responsibilities will include mathematical modeling, algorithm design, software prototyping, and running Monte Carlo simulations in a network traffic domain. Candidates should be strong scientific programmers and have some background in numerical optimization, simulation design, and auction theory.