Internship: Nonlinear Estimation of Multi-physical Systems

MERL is looking for a highly motivated and qualified candidate to work on estimation of multi-physical systems governed by sets of differential algebraic equations (DAEs). The research will involve study and development of estimation approaches for large-scale nonlinear systems, e.g., vapor compression cycles, with limited sensor availability. The ideal candidate will have a strong background in one or multiple of the following topics: nonlinear control and estimation, sensor selection, optimization, and active learning; with expertise demonstrated via, e.g., peer-reviewed publications. Prior programming experience in Julia/Modelica is a plus. Senior PhD students in mechanical, electrical, chemical engineering or related fields are encouraged to apply. The typical duration of internship is 3 months, and the start date is flexible.

Research Areas: Control, Dynamical Systems, Optimization

Contact: Vedang Deshpande

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