215 computing-"https:"-"https:"-"https:"-"UCL"-"UCL"-"UCL"-"UCL" positions at Zintellect
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protocols using aerial and ground-based platforms for agricultural safety monitoring. Apply advanced image analysis and computer vision techniques to identify and classify food safety risks in agricultural
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Organization Oak Ridge National Laboratory (ORNL) Reference Code ORNL-ECO-2026 How to Apply Click Apply below Description The Education Collaboration at ORNL Program is offering opportunities
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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 statuses that are acceptable
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, program rules, and availability of the participant. What are the provisions? You will receive a stipend to be determined by DEVCOM-CBC. Stipends are typically based on a participant’s academic standing
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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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educational level and experience. The anticipated stipend range is $102,415 - $121,785 annually. Citizenship Requirements: This opportunity is available to U.S. citizens only. ORISE Information: This program
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and gene therapies. Research Project: You will join a research program that: (i) Investigates the mechanism(s) of coagulation in the context of drugs used to treat bleeding disorders. (ii) Develops
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mycobateria and brucella families in various species of animals using serological tests as part of the eradication program. Learning Objectives: The participant will have the opportunity to learn about zoonotic
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about integrating traditional biological research with modern computational approaches. The successful candidate will join an interdisciplinary team of plant pathologists, geneticists, molecular
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cannot be feasibly built across the wide range of environmental conditions present in U.S. croplands. To address this, computer simulations can evaluate the performance of different cropping systems across