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atomization, droplet formation, and transport processes; applying quantitative image analysis and scientific programming techniques; comparing experimental observations with computational models; and
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for developing and using systems to phenotype root systems in greenhouse and field settings under the guidance of research mentors. Build skills in root image processing and other data analysis activities using
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therapeutics. The experience includes opportunities to learn the operation and upkeep of physiological and cell culture instrumentation, apply quality assurance and quality control practices, and contribute
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will learn how to use and maintain specialized equipment for measuring gas exchange and collecting image-based and spectral data used to evaluate plant performance and stress responses. You will also
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the nonlinear Hall effect, could potentially explain the observed experimental OR current. Using experimental probes such as x-ray and other material analysis techniques, imaging, probe-based microscopy, visible
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-Informed Neural Networks (PINNs) and hybrid models that respect the physical laws governing the real-world system Applying Deep Reinforcement Learning (DRL) algorithms to optimize processes within simulation