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: This research project aims to investigate the capabilities of long-read next-generation sequencing (NGS) technologies for adventitious virus detection in a complex matrix mimicking a biological test material. The
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, such as atmospheric composition, and/or 2) Experience in forward models, which can take many different forms (e.g. climate, chemistry, cloud), as well as levels in complexity (e.g. 1D to 3D). However, we
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within interdisciplinary teams and engage with researchers, veterinarians, and industry stakeholders to address complex questions in animal disease management. Mentor(s): The mentors for this opportunity
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areas. This fellowship places a strong emphasis on the application of machine learning, artificial intelligence, and bioinformatics to solve complex biological problems. Potential research activities may
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assembly, population genetics, statistical genetics, complex trait mapping, and high throughput sequencing genome and programming proficiency in R, Python, Perl, C/C++, Java, and SAS are highly desirable
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complex biological systems, and communicate clearly in a collaborative environment Stipend $87,803.00 Yearly Point of Contact Janeen Eligibility Requirements Citizenship: U.S. Citizen Only Degree: Doctoral
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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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and their natural enemies. This research will leverage advanced 'omics' technologies and 'big data' analytics to unravel complex pest-natural enemy interactions, understand host associations, and
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to integrate diverse perspectives and convergent methods in addressing complex social dimensions of wildland fire management. Mentor: The mentor for this opportunity is David Flores (david.flores2@usda.gov
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will also consider fire exposure risk, erosion, nearshore coral health, and health and human safety. This learning opportunity will involve mentorship into how to construct complex landscape scale