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. The successful candidate will also apply statistical modeling for mechanistic inference and conduct biogeographic and geospatial analyses of microbiomes. This position involves collaborating with scientists and
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preparation of samples for projects involving process optimization, automation, and data-driven materials discovery. This position is primarily intended for a researcher with strong hands-on expertise in
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the instrumentation, developing the data analysis methods, and applying the methods to study model biomolecules and biomass systems. This research is part of the laboratory’s work for an Office of Science, Biological
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, and trusted to deliver innovative, science-driven solutions to the most pressing challenges in animal health and food production. We advance our vision by empowering current and future veterinarians
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for renewal. Required Minimum Qualifications: Ph.D. in chemistry, chemical engineering, or materials science engineering must be completed prior to start date. Demonstrated extensive experience synthesizing
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collaborative and multidisciplinary environment, the postdoctoral researcher will investigate viral-host interactions using a variety of molecular biology approaches and both ex vivo and in vivo model systems
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, Genomics, Genetics, or equivalent. Experience working in plant model systems A demonstrated track record of publishing independent research, including at least one first-author peer-reviewed manuscript
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objectives, prepare technical reports, and achieve sponsor-defined milestones outlined in the statement of work. Required Minimum Qualifications: Ph.D. in Chemistry, Materials Science, Chemical Engineering, or
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, national laboratories, or industry. Required Minimum Qualifications: Ph.D. in chemistry, materials science, pharmaceutical sciences, chemical engineering, physics, or a closely related field. Preferred
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metabolomics datasets. Research activities will include both targeted and non-targeted metabolite profiling of a wide range of sample types, including animal models, human cell lines and cohorts, plants