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the Arctic, experimental tests of climate driven changes in carbon export from land and turnover and release of greenhouse gases (CO2 and CH4 ) from headwaters, and use of machine learning and process-based
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Innovative city . The position is formally based at the Division of Statistics and Machine Learning (STIMA) within the Department of Computer and Information Science . At STIMA, we conduct research and
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the condition of Swedish surface waters with respect to water chemistry, pollution and aquatic biota. The research focuses on geochemical and hydrological processes, aquatic ecology and biodiversity, microbial
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Fraunhofer-Chalmers Centre (FCC) is a leading research centre in industrial mathematics, modelling, simulation, optimisation, and data analytics. We operate at the interface between academic research and
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fields) with a focus on farm animal behaviour and welfare. interest and/or experience in animal behaviour, experimental studies, statistics, and computer-based data analysis. strong communication skills in
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research on raw materials, materials, processes, and systems to contribute to the sustainable development of forest resources and a circular bioeconomy. The department is located on campuses in both Umeå and
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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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membrane separation processes for separation of fat and proteins, as well use a number of techniques for physico and chemical charaterisation of the streams obtained. Experience within these fields is a
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such as satellites, LEO constellations, fixed links, automotive radar, and Earth observation stations, using techniques from signal processing, communications theory, optimization, and AI. You will join the
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complex systems. Development and application of theoretical tools that combine experimental data and atomistic computer simulations to provide a comprehensive picture that is difficult to achieve through