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with deep learning models such as autoencoders and neural networks. Experience with ecological, geospatial, or movement data (e.g., GPS telemetry). Strong oral and written communication skills, including
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will also consider fire exposure risk, erosion, nearshore coral health, and health and human safety. This learning opportunity will involve mentorship into how to construct complex landscape scale
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newly established network of experimental silviculture and genetics plots while leveraging existing long-term studies and datasets to meet urgent questions in the near-term. The research fellow will
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. NAMRU-SA serves as one of the leading research and development laboratories of the U.S. Navy under the Department of Defense and is one of eight subordinate research commands in the global network
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of the appointment start date. Preferred Skills: Experience in bioinformatics and computational analysis across prokaryotic and/or eukaryotic systems, with experience addressing complex biological questions related
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establishing a soil moisture monitoring network within agricultural fields for validating NISAR products. The second goal is for the candidate to learn about new technologies in radar and optical remote sensing
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collaboration with other USDA and non-USDA researchers to address complex questions in agriculture will be available. Additionally, opportunities to develop soft skills to enhance career success will be available
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an opportunity to receive hands-on experience in navigating the complex molecular interface of plant-pathogen interactions. The participant will be encouraged to analyze experimental data, troubleshoot complex
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agency Develop skills in interacting with agency partners to develop applied science to meet complex forest management, harvesting, and utilization objectives. Develop analytical skills analyzing forest
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to develop skills in manuscript preparation, research presentation, and domestic and international collaboration with other USDA and non-USDA researchers to address complex questions in livestock disease