109 machine-learning-"https:"-"https:"-"https:"-"https:"-"UCL" Fellowship positions in Norway
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- University of Oslo
- University of Stavanger
- NTNU - Norwegian University of Science and Technology
- University of Agder
- University of Bergen
- UiT The Arctic University of Norway
- CICERO Center for International Climate Research
- CMI - Chr. Michelsen Institute
- Høgskulen i Volda
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- University of Oxford
- Østfold University College
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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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methodologies Experience with machine learning techniques Experience with pipeline development and testing (gitlab, simulated light curves…) Ability to work independently and to collaborate in an international
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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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measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models
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completed a doctoral degree in (machine learning, statistics, or similar). You must have a professionally relevant background in algorithms, machine learning, database systems, or data mining. Experience with
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to acquire during the employment period. The Postdoctoral Fellow will also have access to career guidance throughout the postdoctoral period. The qualifying project will be carried out at the University
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or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models in small samples. The appointment is a full-time position and is made for a period of three years
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for three years with research duties exclusively. A career plan will be prepared that specifies the competencies that the Research Fellow will acquire. Access to career guidance will be provided