Internship: Numerical Optimization Algorithms for Predictive Control
MERL is looking for a highly motivated individual to work on efficient numerical algorithms and applications of optimization based control methods. The research will involve the study and development of novel optimization techniques for predictive control and estimation and/or the implementation and validation of algorithms for industrial applications. The ideal candidate should have experience in either one or multiple of the following topics: convex and non-convex optimization, Newton-type optimization algorithms, numerical optimization (e.g. active-set or interior point) and optimal control. PhD students in engineering or mathematics with a focus on numerical optimization or numerical optimal control are encouraged to apply. Publication of results in conference proceedings and journals is expected. Capability of implementing the designs and algorithms in Matlab is required; coding parts of the algorithms in C/C++ is a plus. The expected duration of the internship is roughly 3 months and the start date is flexible.
Contact: Rien Quirynen
Mitsubishi Electric Research Labs, Inc. "MERL" provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, MERL complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
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