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://www.uib.no/en/sefas About the project/work tasks: The postdoctoral research fellow will perform quantitative data analysis using advanced techniques such as signal processing and dynamic systems modeling, and
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models. Both domestic and international travel may be required as part of this role for data collection and participation in workshops, conferences and symposia to communicate research findings. To be
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modeling, hydrological models, and/or climate models. While this topic is the primary focus of the position, the fellow will be encouraged to pursue novel research topics. The successful candidate will join
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lead the in vivo functional analysis of this gene using conditional KO mouse models, with a focus on brain development, neuronal differentiation, and seizure susceptibility. All models are already
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interpretation. This role will involve working closely with civil engineers, computational modellers, Physicists, and geophysicists to translate raw sensor outputs into actionable insights. Role Summary Lead data
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date for the post) Experience in maintaining stem cell culture models, with preference for mouse or human ESCs. Experience in high-throughput (epi)genomics assays or related technologies. Experience in
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of productive and creative research, demonstrated by presentations at scientific conferences Experience in developing system-scale models of water treatment technologies Experience constructing datasets required
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SUMOylation, transcription factors, or chromatin dynamics. Expertise in machine learning or statistical modeling for biological data. Knowledge of enhancer-promoter interactions and 3D genome organization. All
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(DPPs) as a key enabler of circular business models, aiming to reduce CO₂ emissions and improve resource efficiency through enhanced data-driven lifecycle management. A DPP can be viewed as a structured
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represents the first dedicated cancer immunology centre in the UK. The activities in this centre span from pioneering discovery science to applied research and preclinical modelling and, crucially, onto first