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The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in machine learning for advanced peatland mapping, starting 01-12-2025 or as soon as possible
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The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in machine learning for advanced peatland mapping, starting 01-12-2025 or as soon as possible
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. Experience in phase-contrast and/or dark-field x-ray imaging. Experience in working with photon-counting x-ray detectors Experience with scanning x-ray imaging such as SAXS mapping, SAXS tensor tomography
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The Dutch Autism & ADHD Research Center is looking for a Postdoctoral Researcher to join an innovative project focused on precision functional imaging in autism. This project breaks away from traditional large-sample approaches to study fewer individuals in unprecedented detail, leveraging an...
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 2 months ago
data to estimate and map above ground forest structure, biomass, and changes driven by anthropogenic and climate forcing. The candidate will participate with a team of scientists conducting original
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candidate will play a pivotal role in advancing our research project focused on leveraging hyperspectral remote sensing for soil fertility mapping and crop nutrient management in selected African nations
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engasjerende for den enkelte brukeren, og dermed mer verdifulle for utgivere og tredjeparts-annonsører. Databehandlingsansvarlig: Youtube, Google Formål: Samler informasjon om brukerne og deres aktivitet på
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Summary Whole brain activity mapping of the maternal (rat) brain (on opioids). Opioid use disorder (OUD) is a global epidemic affecting a high proportion of child-bearing women. The drastic 4-fold
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Job Summary Are you passionate about applying cutting-edge GIS Mapping and Water Quality modeling techniques to address critical environmental challenges? Join us in an exciting initiative aimed
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for data-efficient exploration and optimization within the process parameter space as well as for adaptive, data-driven machine learning to map the electrolysis process to a digital twin. Data workflows and