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, economic evaluation, and surveillance to learn how to operationalize, and when needed, improve analytical tools. Research activities will support rapid risk assessment, emergency preparedness, and
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attenuated centrin deleted Leishmania major parasites (LmCen-/-) using transcriptomic and metabolomic approaches. Learning Objectives: The opportunity to contribute on this project will allow you to acquire
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machine learning, data analytics, or computational biology. The ability to research independently as well as collaboratively, and a record of scientific productivity. Stipend $70,000.00 – $80,000.00 Yearly
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, gaining insight into how diverse fields collaborate to address complex problems. They will also learn how to effectively integrate multiple data sources and apply a range of analytical techniques
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the one of the relevant fields. Preferred skills: Experience in forest operations analysis, forest resource management, spatial data science, supply chain/logistics analytics, machine learning Analytical
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motivated Postdoctoral Research Fellow for a learning opportunity using cutting-edge genomic and transcriptomic methodologies to drive innovative biological control strategies against high-impact invasive
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. Research integrates analytical chemistry, microbiology, entomology, and engineering approaches and is conducted in collaboration with agricultural stakeholders and industry partners. Learning Objectives
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using different LC/MS or GC/MS based techniques. Learning Objectives: As a result of this training, you will gain knowledge and experience in: Liquid chromatography, gas chromatography, and the hyphenated
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students and collaborate on aquatic ecology field projects in southeast Alaska wilderness watersheds. Learning Objectives: Learn about bioenergetic food web models to quantify food web energy fluxes between
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to: Learning about aircraft systems engineering and systems analysis to support integrated design and performance assessment. Participating in aircraft design trade studies with a focus on propulsion–airframe