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quality models, especially for coastal water environments You must be highly proficient in the use of programming languages including, but not limited to python, C++, but also database management
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Title: Predicting and Improving the Quality of Recycled Plastics Using Advanced Metrology and Data Science Research theme: "Materials Characterisation" "Data Science and Machine Learning in
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utilized to mitigate flooding risks through hydrological modelling and stakeholder engagement.Focusing on the Gothenburg region, the project will: Identify roads suitable for climate adaptation in three
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microscopy to produce new knowledge with immediate implications for the design and function of water-based systems for electrosynthesis. Objectives Key objectives include addressing conceptual and technical
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, fisheries, aquaculture or the deep sea. The PhD project will focus on how to govern these new models of representation – in other words how to design the ‘rooms’ and which dynamics of the rooms make decisions
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prone to change and decline. One project component analyses and models the effects of climate-induced cryospheric changes on water flows. The other project component, to which you will contribute
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change, the sustainable use of the world's coastal systems and the resource-compatible enhancement of the quality of life. From fundamental research to practical applications, the interdisciplinary
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communication for global ocean environments: Deep learning models perform robustly on certain environments since they are developed by data in low signal-to-noise ratio. To develop more robust models, we will
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an essential component in the safe and reliable operation of Generation III+ and IV nuclear reactor designs, including High Temperature Gas-Cooled reactors (HTGR), Pressurized Water Reactors (PWR), Lead-Cooled
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biodiversity. Specifically, the primary focus of the PhD will be to analyse and parameterize models describing the ecological and evolutionary dynamics of small and fragmented populations, and how the risk of