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: The U.S. Geological Survey (USGS) increasingly relies on efficient, scalable administrative processes to support its broad scientific mission across field, laboratory, and data-driven research environments
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datasets depicting the perception and resilience of the natural and engineered environments supporting the industry. The overarching goal is the creation of broadly applicable datasets describing emerging
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to organize and manage multiple assignments while acting independently and collaboratively in a multidisciplinary environment. Interest in environmental trends, environmental public health, health equity, and
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hazardous waste; and ensuring compliance with Environment, Safety, and Occupational Health (ESOH) standards and other environmental permits. This project will involve research activities that will enable
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concepts to technical and non-technical audiences. Demonstrated ability to organize and manage multiple assignments while acting independently and collaboratively in a multidisciplinary environment. Interest
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the ability to identify food safety challenges associated to food processing environments Mentor(s): The mentor for this opportunity is Luz Daniela Bermudez-Aguirre ([email protected] ). If you have
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to translating these results into peer-reviewed scientific studies. Experience using multiple bioinformatic pipelines in high-throughput computing environments and implementing these pipelines and additional
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with Artificial Intelligence (AI) techniques to improve model performance and predictive capability. Gain exposure to multidisciplinary and collaborative agricultural research environments involving
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propagation and/or imaging in complex battlefield environments. As signals propagate through the environment, they undergo effects due to atmospheric turbulence, atmospheric gradients, terrain, and other
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controlled laboratory environments, greenhouse facilities, and natural field conditions. Gain extensive training in cutting-edge analytical instrumentation and methodologies, as well as specialized expertise