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Field
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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will conduct the lab experiment for RAS system for pollution control in recycled water in aquaculture system. He/she will also use machine learning tools to predict and optimize the RAS system. Job
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, incorporating electronic, thermo-fluid models, and efficiency models (ii) BMS-BTMS operation policy design, which will be based on optimal control techniques and will focus on both electric power
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, or a related field Extensive experience in the controllable synthesis of nanomaterials. Expertise in machine learning-assisted materials design and process optimization. Expertise in
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writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning and optimization & controls Having basic knowledge in carbon
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technology management, or smart grids. Experience in development of mathematical meta-models, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno
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/experimentation. • Design and develop an intelligent and optimal switching strategies, control techniques, and energy management system (EMS) for the energy efficient and reliable operation. • Perform HIL
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functional devices with applications in biofilm control, structural health monitoring, medical technologies, and beyond. The role emphasizes the integration of acoustic transduction elements (e.g., ultrasound
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and advanced control systems. The position is supported by Michigan Translational Research & Commercialization (MTRAC) Advanced Transportation Program, aimed at addressing power quality challenges in
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on the design and development of power electronics, active harmonic filters and advanced control systems. The position is supported by Michigan Translational Research & Commercialization (MTRAC) Advanced