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for Transportation (VITA ) is looking for a postdoctoral researcher in the area of Generative AI. VITA research interests lie at the intersection of Computer Vision, Machine Learning (Deep Learning), and Human-Robot
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-facing web GIS dashboard. Investigate the forest, landscape, and climate conditions that drive storm susceptibility, using major windstorms as natural experiments and interpretable machine-/deep-learning
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data and deep learning methods to assess canopy cover, quality, carbon stocks, and ecosystem services. Mandatory requirements: PhD in areas related to forest resources, remote sensing, data science, or
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, with a strong interest in the integration of geospatial Artificial Intelligence (AI) and machine learning. Are you enthusiastic about the chance to combine research in Remote Sensing and AI with teaching
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postdoctoral appointment in Remote Sensing of the land surface, with a strong interest in the integration of geospatial Artificial Intelligence (AI) and machine learning. Are you enthusiastic about the chance to
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: Onboarding and Integration, and Innovation and Creative Capacity. The work will focus on investigating how hybrid work arrangements influence learning, collaboration, innovation, and organizational performance
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Magdeburg, Sachsen Anhalt | Germany | 10 days ago
PhD in psychology, neuroscience, cognitive science, biostatistics, or a related field Passion for cognitive research and neuropsychology, and a genuine interest in cognitive
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for this job position. Additional Information: Minimum Requirement: PhD in psychology or related area. Location: Remote Location Position Type: Term (Fixed Term) Scheduled Hours: 40 Shift: First Shift Final
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, as well as a large community of PhD students, postdoctoral researchers, and other research associates. The laboratory conducts internationally recognized research in atmospheric chemistry, air quality
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National Aeronautics and Space Administration (NASA) | Huntsville, Alabama | United States | 18 days ago
to advance use of foundation models for Earth Science research and applications, including fine-tuning experiments Use of remote sensing, models, and/or machine learning to further our understanding