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and time. In this project we will model the ionosphere-ground system with a unique time-domain model which is developed in the group for ’Solar-Terrestrial Physics and Space Weather’ at the Department
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of pathogens, their interactions with hosts and the environment, and how they are transmitted through populations. Research will have a strong focus on computational analysis or predictive modelling of pathogen
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experimental cellular and molecular biology techniques, as well as in vitro, in situ, and in vivo model systems. Eligibility requirements To be admitted to doctoral studies, the applicant must meet both
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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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or post- transcriptomic mechanisms of plant plastic response to stress using wild Arabidopsis thaliana ecotypes as a model. The successful candidate will have the opportunity to work on a cutting-edge
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are of interest. The primary objective of this PhD project is to develop adaptive statistical models for marked spatial and spatio-temporal point processes. Many real-world systems exhibit substantial spatial
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. Research will have a strong focus on computational analysis or predictive modelling of pathogen biology or host-microbe systems for which multidimensional, genome-scale experimental data are now available or
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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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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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and other key actors, the project explores which governance models and policy instruments are most effective in achieving multiple objectives. The goal is to generate new knowledge about how forest