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Field
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conferences and learn appropriate scientific methods and procedures. Among the key duties of this position are the following: Carry out multiphoton optogenetic manipulation and imaging of neural activity in
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and/or Work Experience M.D. or PhD Required Qualifications M.D. or PhD Required Certificates/Credentials/Licenses M.D. or PhD Required Computer Skills N/A Supervisory Responsibilities Yes Required
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to the marketplace. Read more: https://www.energy.gov/technologycommercialization/office-technology-commercialization About this Opportunity The fellowship is offering candidates the opportunity to learn about the
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policy-related appointment. The DOE Office of State and Community Energy Programs (SCEP) is seeking ORISE fellows to participate in a community-based opportunity. Fellows will learn about technical
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Charles Henry Turner Post-doctoral Fellow, Department of Geography & GIS, College of Arts & Sciences
a closely related field Background in GIS, remote sensing, hydrology, environmental resource management, public health, urban digital twin, or data visualization Expertise in GeoAI/machine learning
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artificial intelligence (AI) and machine learning (ML) methodologies and interested in advancing these tools for accelerating the analysis of the big data acquired by electron microscopy. • You work
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technologies and how their technology use impacts their relationships and well-being, and on the application of machine learning in family and developmental research. The Post-Doc will contribute to Dr. Sun’s
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-level understanding of kinetics in solid-solid phase transitions; Develop advanced machine learning methods for the fast prediction of materials properties; Publish results in peer-reviewed journals and
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, computer science, machine learning, and education research. Research Themes The research themes identified for the NTO postdoc include, but are not limited to, the following: Developing or evaluating methodologies
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rise (SLR) and flooding. Integrate field data (e.g., salinity, nutrient levels, soil and water properties) into the development of numerical models to enhance predictive accuracy. Apply machine learning