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responses and microbial persistence. Learn to design, train, and iteratively refine machine learning models to learn distinguishing features of true microbial contaminants versus host-derived and process
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a fellow to collaborate with other Unit scientists and University collaborators, performing a wide range of activities designed to solve problems related to the two-spot cotton leafhopper (Amrasca
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Requirements Degree: Any degree . Discipline(s): Business (11 ) Chemistry and Materials Sciences (12 ) Communications and Graphics Design (6 ) Computer, Information, and Data Sciences (17 ) Earth and
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. Research Proposal o Research topic should relate to a specific opportunity at ARL o The objective of the research topic should be clear and have a defined outcome o Explain the direction you plan to pursue o
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. Research Proposal o Research topic should relate to a specific opportunity at ARL o The objective of the research topic should be clear and have a defined outcome o Explain the direction you plan to pursue o
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and epigenetic variation from sequencing datasets in livestock species. Design and implement statistical methods for QTL mapping and association studies, and interpret their results in the context
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pathogens, such as those causing wheat blast and soybean red leaf blotch. Acquire skills in collecting, processing, and analyzing whole-genome sequence data. Learn to design, develop, and optimize fungal
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Engineering 1: Under the guidance of a mentor, this Lifecycle Engineering program area will teach you how to utilize chemical, biochemical, and systems engineering to develop and design solutions that continue
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fungal ecology, physiology, and genetics. Experimental Design: You will gain experience in hypothesis-driven experimental design. This will include selection of biologically relevant treatments to assess
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also assist in designing and conducting all aspects of the experiment under the direction of ARS scientists. This includes evaluation of the survival of various foodborne pathogens on selected fresh and