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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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fellow at the same institution. For all LEAD AI fellows, a Personal Career Development Plan (PCDP) will be developed jointly by the fellow, supervisor, and co-supervisor by the end of Month 3
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with researchers at Haukeland University Hospital and The Western Norway University of Applied Sciences. A part of the interdisciplinary collaborations is focused on development of diagnostic methods
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collaborations is focused on development of diagnostic methods based on magnetic resonance imaging (MRI). The PhD candidate will work on a project where the goal is to develop methods (acquisition and processing