Internship: Embedded optimization algorithms for realtime control
MERL is looking for highly motivated individuals to implement real time optimization algorithms on embedded platforms. The ideal candidate is a MS or Ph.D. student in electrical and computer engineering or computer science with experience developing applications for embedded and real time platforms. Proficiency in C/C++, Matlab, and embedded systems is required. Experience with real time systems is preferred and familiarity with model predictive control or convex optimization algorithms is a plus. The duration of the internship is 3-6 months. Start date is flexible between January and July 2017.
Research Area: Mechatronics
Contacts: Dan Burns
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