191 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" Fellowship positions in Norway
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- University of Oslo
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- NTNU Norwegian University of Science and Technology
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. Any appointment is conditional upon submission of documentation confirming completion of the PhD degree. solid programming skills applied to machine learning algorithms, interactive systems, audio and
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international profile. Questions about the position Andreas Carlson, Web: https://acarlson-uio.github.io Professor +47 22857223 acarlson@math.uio.no For technical questions related to the application portal
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equations, functional analysis, and stochastic analysis. For more information about the project, see here: https://www.mn.uio.no/math/english/research/projects/nastran/index.html Francesco Saggio/UiO via
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participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s mission is to establish an internationally leading
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solvers, with the goal of exploiting models of various complexity, ranging from high-performance computing, via reduced-order models to data-driven (machine-learned) representations. In particular, we
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resulting precipitation and extreme weather. We study global and regional climate change and are at the core of international community climate modeling efforts that also involve AI and Machine Learning. We
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to: compositional multiphase reservoir simulation upscaling or screening methodologies optimization of well positions and control strategies economic assessments machine learning or proxy-model based methods field
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responsible machine learning and/or human-AI interaction can be integrated with music-based forms of human creativity to contribute to health and well-being. The doctoral research should address one or several
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to investigate how responsible machine learning and/or human-AI interaction can be integrated with music-based forms of human creativity to contribute to health and well-being. The doctoral research should address
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. In addition, you must have: a solid foundation in energy technology and a strong understanding of artificial intelligence (AI), machine learning (ML), and data-driven modeling documented experience