265 machine-learning "https:" "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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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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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
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, the participant will learn HPC computing technologies and techniques in genomic epidemiology and machine learning to quantify drivers of IAV evolution in swine using data generated from IAV surveillance in human
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online databases or interactive websites. Learning Objectives: TUnder the guidance of a mentor, the participant will learn techniques in genomic epidemiology and machine learning to quantify drivers of IAV