261 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at Zintellect in United States
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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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improving plant health using machine learning and artificial intelligence. Mentor(s): The mentor for this opportunity is Yulin Jia (yulin.jia@usda.gov ). If you have questions about the nature of the research
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culture of teamwork, as such you will learn how to be a member of a laboratory team and how teams of researchers accomplish common research goals. Why should I apply? Under the guidance of a mentor and
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Residents of the United States. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control . Questions about this opportunity? Please email npp@orau.org Qualifications
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information on the IHS Division of Sanitation Facilities Construction program can be found at https://www.ihs.gov/dsfc/ . Learning Objectives: Under the guidance of a mentor, you will gain hands-on experience
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. Along the way, you will engage in activities and research in many areas, including, but not limited to: Learning small and large animal behavioral assessment techniques Developing skills in physiological
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Countries will not be accepted at this time, unless they are Legal Permanent Residents of the United States. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control
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library into the Bios platform Gain applied experience in software validation, ensuring CDS features are successfully and reliably incorporated into the final tool used by medics Learn from engineering and
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educational activities and research in several areas. These include, but are not limited to: Learning to use instruments that provide precise measurements of high frequency phenomena Developing new
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, biochemical, and gene expression data to determine underlying biological mechanisms Learning how artificial intelligence models can interpret biological data Documenting and writing detailed methods and results