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) and contribute to LU-PCG’s research under the U.S. Department of Energy’s (DOE) GENESIS Mission. Research will involve developing fast neural surrogate models, state estimators/virtual sensors, multi
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benefit trade-offs of sensor and actuator layouts, e.g., for improved ventilation. Hybrid data-driven and model-based control algorithms for improved online decision-making, e.g., for ventilation
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well as agritech sensors. Procure experimental equipment, sensors, and peripherals. Maintain data pipelines for greenhouse and CEA experiments, including adapting source code to different crop types (e.g., camera
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