68 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" Fellowship positions in Norway
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representation through machine learning. The position is for a fixed term of 3 years and is part of the project “Reaching AI Projections Trustworthy for Unseen Rainfall Extremes (RAPTURE)”, funded by a European
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interpretable machine learning framework that integrates diverse biological data—including transcription factor (TF)–DNA interactions, epigenomic features, and three-dimensional (3D) genome organization
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that are deeply grounded in stochastic analysis and show also development of computational methods towards machine learning. The projects will focus on applications to risk-sensitive decision making and control
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or human-computer interactions studies. The focus of the PhD-thesis needs to contain knowledge areas such as learning theory, cognitive theories with applications on studies of learning, design of learning
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that are deeply grounded in stochastic analysis and show also development of computational methods towards machine learning. The projects will focus on applications to risk-sensitive decision making and control
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structures or subcortical areas Experience in applying machine learning in neuroscience Experience in analyzing large MRI dataset Familiarity with analyses of structural MRI data (volumetric and/or DTI
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on addressing this question which lies at the heart of understanding high-impact flooding in an ever warmer and wetter world. RAPTURE brings together high resolution physical simulations, machine-learning climate
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many areas of applied and theoretical statistics and data science, and is heavily involved in research at the crossing of statistics and machine learning. The focus of this postdoctoral fellowship is to
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with remote sensing data (satellite, aerial, hyperspectral, SAR, LiDAR) Computer Vision Natural Language Processing Remote Sensing Machine Learening and Deep Learning Reinforcement Learning Large
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, Julia, C/C++ or similar is required. Experience with machine learning, analysis of climate or high-resolution model output, climate predictions/projections or environmental risk assessment is an advantage