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promoters. Digital Phenotyping: Application of hyperspectral imaging and advanced imaging tools to detect disease traits beyond the visible spectrum. AI-Driven Data Analysis: Leveraging machine learning
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management of field plot trials, data collection, and database management. Experience in large data analyses Experience with operation optimization Experience with machine learning, image analysis Experience
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phenotyping using both drone-based and ground based sensing platforms. Learn artificial intelligence and machine learning techniques to analyze image and geospatial data from diverse sources for crop monitoring
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Raman imaging technologies for safety and quality evaluation of agricultural products. Learn artificial intelligence/machine learning methods to evaluate hyperspectral image data to assess safety and
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machine learning, image recognition, and prediction of damage to tree nuts from insect pests. They will also collaborate with other team members on statistical analysis of data collected as part of
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areas. These include, but are not limited to: Applying machine learning algorithms to solve real-world problems. Creating and structuring databases for storage, retrieval, and image analysis. Determining
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received a master's or doctoral degree in the one of the relevant fields Preferred skills: Experience/education in python, R, or other computer programing and statistics tools Education/experience in any
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Materials Sciences (12 ) Communications and Graphics Design (2 ) Computer, Information, and Data Sciences (4 ) Engineering (3 ) Environmental and Marine Sciences (2 ) Life Health and Medical
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readiness Theory and application of machine learning and artificial intelligence including predictive maintenance, predictive logistics, statistical analysis of production data, statistical process control
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within the last 60 months or currently pursuing. Discipline(s): Chemistry and Materials Sciences (12 ) Communications and Graphics Design (6 ) Computer, Information, and Data Sciences (17 ) Earth and