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properties of catalysts together with statistical methods to derive predictive models for selective catalysis. In a data-driven approach, an initial set of reactions is analyzed and used to establish such a
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Vacancies PhD Candidate Geospatial Risk Modelling for Climate Finance Key takeaways Effectively understanding and mitigating financial risks associated with climate change is important for
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), sustainable, and climate-adaptive crops. By combining plant biology, simulation modelling, and artificial intelligence we aim to develop smart breeding and cultivation methods. Thus, we try to speed up
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computational models that learn by finding patterns in language data. Can they learn the different modal meanings simply by paying attention to what they “hear”? Or do they need to come prepared with certain
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Vacancies PhD Position in Computational Biology: Digital Twins & Disease Modeling for Precision Osteoarthritis Treatments Key takeaways Osteoarthritis (OA) is a complex disease in which multiple
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to train an AI model that predicts the cis-regulatory code for synthetic genomes (i.e. for cell-free gene expression systems) and correlates the experimental conditions within the synthetic cell
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gyre (SPG) and Arctic and Antarctic sea ice cover, involving processes on smaller scales, which are often not well represented in modelling efforts focusing on the large scale tipping elements
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models combined with the finite element method. Constitutive relations are required to describe material behavior. Advanced stainless steel typically possess complex microstructures across various length
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affect regional agriculture and transport and possibly global food security. Recently, researchers from IMAU have for the first time modelled a full AMOC collapse in a full-fledged climate model
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based hydrological modelling with observational data. The research involves setting up an integrated hydrological model that collects both vertical and lateral hydrological processes, from the atmosphere