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psychology; narratives and communication; Earth system risks and tipping points; or experimental and intervention-based social science. Experience with empirical data collection and analysis, participation in
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companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
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nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
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sequencing data generation and interpretation Bioinformatics and statistical analysis, to characterize genome evolution, mutation processes, and adaptation patterns The PhD candidate will progressively
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cellular biology techniques, including nucleic acid manipulation, cloning, gene expression analysis, CRISPR-based approaches, protein analysis, and functional cellular assays. Extensive hands-on experience
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, informal communities, and more-than-human constituencies. The PhD student will combine conceptual research, community-centered design, qualitative analysis, co-creation, and design-oriented knowledge
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Analysis and Architecture (LAAS) within the MechaBioFluidics team, which has extensive expertise in microfluidics and microfabrication (a technology platform of the national ReNaTech network), both located
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in one) will be a plus. Background in statistical learning, data analysis, or cybersecurity. Programming skills Proficiency in English [Optional] Experience with NLP or text analysis [Optional
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of flexible hydropower operation on potential internal erosion processes in embankment dams. The research will involve experimental investigations, data analysis, and possible field work, in collaboration with
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from Rolls-Royce plc. This fully funded PhD project, with support from a leading industrial partner, will explore the development of next-generation intelligent sensing and data analysis techniques