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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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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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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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of methane dynamics in rapidly changing ecosystems and contribute to improving predictive models of future methane emissions. Field sampling will focus on regions where methane cycling is still poorly
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reconstruct the structural models, with an emphasis on picking and combining the right techniques, as well as quantifying the uniqueness of information obtained. Position Overview: You will develop an in-house
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palynology and organic biomarker and biogenic calcite geochemistry at several sediment sequences. You will collaborate with fellow PhD candidates or postdocs carrying out climate model experiments
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://romeijn.web.rug.nl/paper/2023_romeijn_-_VICI_project_description.pdf ), where you can find a detailed list of planned PhD and postdoc positions. Candidates can freely choose their research topic within the domain