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the Department). The position is financed by the University of Bergen. About the project/work tasks The PhD project aims to investigate how methods from Scientific Machine Learning (SciML) can enhance modelling
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), (c) estimation methods for latent variable models (e.g., two-step approaches or approximate maximum likelihood estimation), or (d) meta-analytic models to address complex data structures (e.g., spatial
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-based computed tomography, with numerical simulations informed by microstructural data. The successful candidate will work at the interface between experiments, modelling, and data-driven methods
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tomography, with numerical simulations informed by microstructural data. The successful candidate will work at the interface between experiments, modelling, and data-driven methods. Particular emphasis will be
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cooperation with the Institute of Marine Research. The core of the position will be on development of new deep learning methods for segmentation/classification of data with limited and weak labels. Your may
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., probability, analysis), eager to conduct cutting edge research in the field of uncertainty quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves
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The position An exciting postdoctoral position in method development for spatio-temporal medical data is available in the UiT Machine Learning Group at the Department of Physics and Technology . Goal: Develop
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, cheating, or careless responding), (c) estimation methods for latent variable models (e.g., two-step approaches or approximate maximum likelihood estimation), or (d) meta-analytic models to address complex
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of Computer Science and affiliated with the Information Systems and Human–Computer Interaction (ISCHI) research group. Your immediate leader will be the unit leader of the Information Systems and Human–Computer
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is also a Principal Investigator at the Hylleraas Centre for Quantum Molecular Science, a Norwegian Centre of Excellence dedicated to the development and application of advanced computer simulations