106 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "https:" "https:" "Dr" "P" research jobs at Zintellect in United States
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publish the results of these projects in peer-reviewed scientific journals. Mentor(s): The mentors for this opportunity are Dr. Jianwei Qin (jianwei.qin@usda.gov ), Dr. Moon Kim (moon.kim@usda.gov ), and Dr
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are Dr. Lina Castano-Duque (Lina.Castano.Duque@usda.gov ) and Dr. Matthew D. Lebar (matthew.lebar@usda.gov ). If you have questions about the nature of the research, please contact the mentor(s
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production systems, soil ecology, forage production, forage quality, nutrient management, and ecosystem services. Research Project: The perennial grass breeding program at the USDFRC develops cool and warm
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to improve soybean for enhanced disease tolerance by accelerating breeding programs and enabling the engineering of new and improved traits. Learning Objectives: As a result of this experience, the participant
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landscape scale Preparing and submitting peer-reviewed publications Preparing and presenting presentations at scientific and stakeholder meetings Mentor(s): The mentor for this opportunity is Dr. Hannah J
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-USDA researchers to address complex questions in livestock disease transmitted by arthropods will be available. Mentor(s): The mentors for this opportunity are Dr. Lee Cohnstaedt (Lee.Cohnstaedt@usda.gov
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of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: One of the primary objectives of the Current Research program at USDA-ARS Southern
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Residents (LPR), and foreign nationals. Non-U.S. citizen applicants should refer to the Guidelines for Non-U.S. Citizens Details page of the program website for information about the valid immigration
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availability, project assignment, program rules, and availability of the participant. What are the provisions? You will receive a stipend to be determined by ERDC-EL. Stipends are typically based on a
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tolerance for varietal selection. Learning Objectives: Participant will gain laboratory, field, and programming skills to develop the digital twin and other AI models using ground and above-ground sensors and