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duties at the Department). The position is subject to financing by NFR. About the project/work tasks: The successful candidate is involved in developing ensemble learning strategies for cell-type
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NFR. About the project/work tasks: The successful candidate is involved in developing ensemble learning strategies for cell-type deconvolution to improve performance and to provide error estimates
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intermittent. The PhD will work will be twofold. The first part will be to improve and develop datasets and estimation algorithms for renewable energy that will enhance the simulation capabilities of the open
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develop datasets and estimation algorithms for renewable energy that will enhance the simulation capabilities of the open-source energy market simulation model for operational planning JulES developed by
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of this project is to develop quantitative and qualitative parameters related to different sustainability dimensions that can supplement data on safe and healthy food with indicators of relevance. The project is a
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tasks: Over time, IMR has built up a large database (Seafood data ) on the content of nutrients and contaminants in various seafood. The aim of this project is to develop quantitative and qualitative
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group actively engages in research encompassing theoretical modeling of quantum systems, the development of optimization algorithms, and the exploration of light-matter interactions. On the experimental
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theoretical modeling of quantum systems, the development of optimization algorithms, and the exploration of light-matter interactions. On the experimental side, we investigate quantum properties of nitrogen
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the doctrinal framework and evolution of the intersection between intellectual property law and artificial intelligence. About the LEAD AI fellowship programme LEAD AI is the University of Bergen's career and
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alarm signal or take other actions locally. We aim to implement methods for quality control and enhancement of data quality through approaches developed in other PhD projects within SFI Smart Ocean. These