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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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PhD in Data-Driven Modeling of Homogeneous Catalysts (1.0 FTE) (V25.0035) « Back to the overview Job description Among the most challenging to develop catalytic reactions are stereoselective
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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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PhD position Modeling modals: A computational study of modal verb acquisition (V25.0196) « Back to the overview Job description The Center for Language and Cognition Groningen is seeking a motivated
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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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, or dynamic models to predict gene regulatory interactions. Work with digital twin technology, simulating patient-specific disease progression and treatment responses. Collaborate in an interdisciplinary
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with researchers from climate physics, hydrology, sustainability science and complex systems dynamics and apply a range of different models. Starting from the recent AMOC tipping simulations performed
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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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drier with global warming. However, particularly in the vulnerable subtropical and mid-latitude regions, the state-of-the-art climate models produce simulations that differ not only in the magnitude, but