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well as physically-based hydrological model development. The principal supervisor will be Ylva Sjöberg at Umeå University, and the research involves an interdisciplinary team of collaborators at Gothenburg University
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instruments used for field measurements. data entry, error checking, data management and GIS work/analysis. organizing and implementation of fieldwork for students. Qualifications We are looking for you with
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and CH4) from headwaters, and use of machine learning and process-based model for large scale assessments and projections of the land-water carbon cycle to variation in climate conditions. The detailed
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transformations. The project investigates a hybrid approach that combines deep learning with grammatical inference to develop models that are interpretable, efficient, and mathematically verifiable while leveraging
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loop/TAD structures. - Perform comparative analyses versus Populus tremula; apply network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce