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SQL databases and file repositories. We are now taking the next strategic step: developing ontologies and a dynamic knowledge graph to semantically link our internal data systems - and connect them
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create multi-fidelity predictive models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train
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Job Description We are seeking an outstanding postdoctoral candidate in the field of theoretical catalysis. The postdoc will be a member of the Catalysis Theory Center (CatTheory) at the Technical
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complex droplet flow patterns and the relations with the chemistry. One successful theory for optimization of surfactant impact and blends is the hydrophilic-lipophilic deviation balance. This enables us to
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learning architectures including generative models, particularly for sequence or structural data (e.g. transformers, graph neural networks) Proved experience in working independently and as part of a
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practice as well as in theory. Your primary responsibilities will include: Investigate, develop and validate new models to simulate wind turbine response in HAWC2 at different fidelity levels. Validation
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-assisted control of large wind turbines. You will collaborate closely with both academic and industrial partners in Denmark and abroad, ensuring that your research has impact in practice as well as in theory
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candidate to help develop these new manners by which to promote bonds as kernels in the interpretation of chemical simulations. For this purpose, novel theory and simulation software will need to be developed
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. During the project, you will work closely together with colleagues in theory who propose optimized designs for your devices, and both receive and provide help to fellow colleagues performing
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partners and optimize them for nonlinear quantum processes Collaborate with theory colleagues to refine fiber designs based on experimental feedback Disseminate results at international conferences and in