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areas within Energy, Climate and Environment and Regional Growth, and integrates the researchers from the Electrical Power Systems (EPS) research group (RG) and Applied Modeling and Control (AMOC) RG
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structural bioinformatics and molecular modeling tools, as well as building on and further developing the datasets and codes from the PePrMInt project (Cf https://doi.org/10.1371/journal.pcbi.1010346
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selectivity of lipid transfer proteins. The project will exploit the wealth of available protein sequence and structure data through analysis using structural bioinformatics and molecular modeling tools, as
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deployment. Existing methods rely on fixed data and static models, which struggle to adapt to real-time changes and unpredictable conditions. This limits the ability to optimize energy storage use for critical
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part of a dynamic research environment focusing on the early mechanisms of neurodegeneration in Parkinson’s disease. The main tasks involve working with mouse models of Parkinson’s disease. Key
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numerical modelling. The PhD candidate’s tasks will primarily be experimental, to conduct hydrate sealing experiments on pore scale and core scale using MRI, but also to provide input for modelling and
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candidate will work in an interdisciplinary research group with both experimental activities and numerical modelling. The PhD candidate’s tasks will primarily be experimental, to conduct hydrate sealing
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. Experience with cancer organoid models and/or bioinformatics is an advantage. We offer broad training possibilities in the required experimental methods within a stimulating academic environment in Centre
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position postdoctoral position within marine biogeochemical modelling at the Geophysical Institute , University of Bergen and the Bjerknes Centre for Climate Research . The position is for a fixed term of 3
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material design process. Some potential key research objectives: AI Model Development: Create machine learning models to predict FGM properties based on compositional gradients and processing conditions