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agencies will broaden your understanding of interdisciplinary collaboration and public-sector science, while reinforcing ethical research practices and the role of science in natural resource decision-making
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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
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towards the development of improved rootstocks for pear production. Research Project: The overall goal of this research project is to characterize root system architecture and root developmental traits
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premier source for data and information on the science and engineering enterprise? Do you want to learn from top researchers and subject matter experts in data analysis, statistics, economics, science
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to adverse growing conditions. You will have an opportunity to gain experience in plant measurements on leaf gas exchange, plant water/nutrient hydraulics, chlorophyll fluorescence, and root system
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conducting a Genome Wide Association Study to identify genetic variants associated with these traits. In the lab, you will help evaluate root growth under heat and drought conditions and develop mapping
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. This creates large uncertainties when modelling orchard water and nutrient fluxes as well as deep percolation below the root zone, critical topics in semi-arid, agriculturally productive regions such as
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and code repositories for open-source software related to UAV imagery processing and ecological community dynamics. You will also have the opportunity to take on-line courses in scientific topics
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such as an research track sprayer, leaf area meter, root scanner, and LI-COR photosynthesis systems; Develop strong competencies in collecting, processing, and analyzing plant samples to characterize
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diverse epidemiologic, clinical, laboratory, genomic, environmental, event-based, and open-source information; explore approaches to rapidly synthesize scientific and public health information during