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of emissions of greenhouse gases. The reason for most of this uncertainty is that clouds are especially challenging to represent in numerical models of the atmosphere. Clouds affect the Earth’s radiation
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IFJ PAN included in my application documents." -a list of scientific and research achievements (e.g. list of publications, conference presentations, completed internships) - 2 letters of recommendation
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IFJ PAN included in my application documents." -a list of scientific and research achievements (e.g. list of publications, conference presentations, completed internships) - 2 letters of recommendation
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PhD Studentship in Aeronautics: How offshore wind farms and clouds interact: Maximising performance with scientific machine learning (AE0078) Start: Between 1 August 2026 and 1 July 2027
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distribution infrastructures, and heterogeneous networks and storage environments based on Cloud based services, CDNs and Edge Computing. This complex chain of delivery has negative implications
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the models; Developed hybrid AI solutions need to be developed and implemented locally as cloud-based solutions are not an option for Thales NL; Working on-site at Thales to: analyse real data, observe current
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part of an international team Desired Qualifications Familiarity with cloud computing platforms and large-scale data processing German language skills Publications in computer vision or machine learning
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to ensure planners and engineers understand, trust, and use the models; Developed hybrid AI solutions need to be developed and implemented locally as cloud-based solutions are not an option for Thales NL
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with deep learning and 3D point clouds Apply for this job See advertisement About the position The Faculty of Environmental Sciences and Natural Resources Management (MINA) at Norwegian University
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) at Norwegian University of Life Sciences (NMBU) has a vacant 3-year PhD–position related to developing deep learning models for 3D forest point clouds. The position is part of "SmartForest" (www.smartforest.no