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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems
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management platform that connects institutes to facilitate a rapid and efficient exchange among experimental and computational groups Devising an approach in invertible predictive modeling that links
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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Management (SLUSE) IPB: Natural Resources and Environmental Sciences (NRES) UPM: Environmental Biotechnology/Environmental Engineering/Environmental System and Modeling UGM: Planning and Management of Coastal
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plant genetic mechanisms that coordinate mycorrhizal interactions with plant P and water status, root system development, and soil microbial communities. Using maize and rice as models, we will: 1
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model complexes. This research is part of a large, funded collaborative project supported by the Swiss National Science Foundation, involving partner researchers based in Germany, Switzerland, and France
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Specifications. The PhD topic consists of two parts, the weighting of which can be adjusted. First, natural frequencies of different UAV categories for different power settings shall be modelled. Second, based
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well as sustainability. Its study model with Leuphana College, the Leuphana Graduate School and the Leuphana Professional School has won numerous awards. For the Institute of Management, Accounting & Finance (IMAF
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coating, iii) investigation of system design from small-scale to potentially pilot scale, and iv) application to micropollutant removal. Modelling aspects are open to exploration at molecular and process