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Army Institute of Research (WRAIR) DoD's premier research enterprise for infectious diseases, brain health, and performance optimization, is offering this Postdoctoral research opportunity to conduct
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Targeted quantitative analysis using triple-quadrupole mass spectrometry Identification and structural characterization of unknown compounds Mass-spectrometry method development, optimization, and validation
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for the identification of molecular mechanisms conferring growth/survival advantages to bacteria in food as well as identify potential biomarkers of persistence. Further activities include troubleshooting and optimizing
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pyrolysis process for producing bio-oils from biomass. The project aims to optimize reaction conditions for microwave pyrolysis of selected agricultural residues and analyze the energy efficiency and cost
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participate in the design and optimize processes to improve ingredient functionality, create distinctive flavors, and eliminate off tastes. Learning Objectives: You will be able to learn from multi-disciplinary
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improved soil quality Incorporating novel approaches to soilborne pest management into existing production systems Optimizing production systems to maximize product quality and nutrition Learning Objectives
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produce Collaborative scientific research and interdisciplinary teamwork Development and optimization of analytical workflows and laboratory methods Communication of scientific findings to research and
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these platforms and to identify potential new markers of anti-malarial drug resistance. Training focus 4: Evaluate and validate the laboratory assays – You will gain experience on the optimization and adaptation
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support systems, protective clothing, precision airdrop systems, and ballistic, chemical and laser-protection systems, and human performance optimization. About ORISE This program, administered by Oak Ridge
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scientists who are highly experienced in their research fields but may not have the technical, information technology (IT), or data science experience to build digital tools that optimize research efficiency