311 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Fellowship positions in Norway
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- University of Oslo
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- NTNU Norwegian University of Science and Technology
- OsloMet – Oslo Metropolitan University
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design and in silico validation intimately connected to experimental validation. In this project, you will develop machine learning methods and apply them in an interdisciplinary environment spanning
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combine intracranial electrophysiological recordings in humans with behavioral experiments and advanced analytical approaches, including machine learning and statistical modeling. It has two main objectives
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at the University of Oslo. Postdoctoral fellows who are appointed for a period of four years are expected to acquire basic pedagogical competency in the course of their fellowship period within the duty component of
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participation in the war in Myanmar since the 2021 military coup d’état. This responsibility includes a mapping of the conflict’s digital war ecology and focusing in on a specific example of remote participation
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), enabling cross-contextual learning and refinement of policy recommendations. A postdoc with expertise in urban built environment studies and qualitative social sciences will play an important role in
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public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills The candidate’s research proposal must be closely connected to the call and the research
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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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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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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