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,” an autonomous environmental robot outfitted with GPS, a downward-facing camera to capture images of surficial sediment, and an onboard machine learning model for image processing. SandHound will be capable
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development, and evaluation, by learning to implement automation, integrating data across systems (SharePoint, Teams, Salesforce, and 1CDP (Palantir System), and creating operational dashboards under
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crop area and learn basic agronomic, data collection, and plant breeding methodologies in trials and nurseries planted at the USDA-ARS. Learning Objectives: The project assignments will provide you with
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learn best practices in instructional design and health communication, including web communication, application of CDC’s quality training standards, user experience, digital content design, and plain
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disease (CWD), other wildlife diseases, and feral swine impacts. You will engage with ecological and wildlife management datasets and learn how quantitative and statistical tools are applied to address real
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medical devices and systems using advanced technologies such as automation, artificial intelligence and machine learning, robotics, telemedicine, advanced displays, computer vision, and data-driven decision
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where new health hazards (such as vapor intrusion or changes in chemical toxicity) have emerged. Learning Objectives: You will have the opportunity to: Learn ATSDR’s approach to conducting public health
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and operations in the following areas: Soil & Groundwater; Deactivation & Decommissioning; Tank Waste; Robotics; Machine Learning; Artificial Intelligence; Cybersecurity; and Advanced Manufacturing
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& Amputation Center of Excellence (EACE) is a unique organization within the Department of War (DoW) consisting of teams of researchers embedded at the point of care within multiple Military Treatment Facilities
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(USAMRDC MRIID). What will I be doing? As an Oak Ridge Institute for Science and Education (ORISE) participant, you will engage in a collaborative learning experience alongside a multidisciplinary community