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engineering, as well as computer vision, imaging, hyperspectral imaging, machine learning techniques in food and agricultural area, is desired. A understanding of modern AI model development Stipend $70,000.00
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various cash and cover crop management practices in U.S. agriculture. Experience in machine learning. Strong computational skills. Strong oral and written communication skills. Stipend $63,940.00
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, microbiology, infectious diseases, animal agriculture, or food safety. Experience in applied statistics, data science, machine learning, mathematical modeling, epidemiology, disease ecology, and PCR assay
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Requirements Citizenship: U.S. Citizen Only Degree: Doctoral Degree received within the last 36 months or anticipated to be received by 9/1/2026 12:00:00 AM. Discipline(s): Computer, Information, and Data
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findings will be encouraged and supported. Learning Objectives: The fellow will have the opportunity to gain or expand skillsets over a range of computational techniques needed for modern agricultural
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biology, statistics, computer science, or a closely related field). Degree must have been received within the past four years. Preferred skills: Computer skills Knowledge and understanding of genome
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advantageous. Additional preference will be given to candidates with computational experience in protein structure–function prediction, metabolic or biochemical pathway analysis, machine learning applications in
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. Develop skills in coupling crop and hydrology models at watershed scales. Gain experience validating models using large, multi-source datasets. Learn to apply high-performance computing and machine learning
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research applying artificial intelligence (AI) and machine learning (ML) techniques to analyze cervid movement patterns. GPS telemetry data obtained from free ranging cervids will be used by the participant
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): Computer, Information, and Data Sciences (2 ) Earth and Geosciences (4 ) Engineering (1 ) Environmental and Marine Sciences (2 ) ORISE GO The ORISE GO mobile app helps you stay engaged, connected and