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& Modeling: Develop and simulate numerical models of damage and failure in aerospace structures, including FEA for metamaterials. Materials Design & Characterization: Study and optimize metamaterials and
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appropriate field. You will work on the project “Data-Driven Micromagnetic Modelling”. Your job This study contributes to SPARK, an ERC Consolidator project that aims to unlock magnetic information stored in
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knowledge through attention mechanisms within transformer networks. Traditional data-driven models struggle with convergence and generalisation due to limited contextual understanding. Earth observation data
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gas analysis, a GC/MS, and an HPLC/MS. DFT calculations will be performed using annual allocations on national high-performance computing centers. More details here: https://iramis.cea.fr/en/nimbe/lcmce
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed
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., Pettersson, H., Behrens, A., Männik A., 2018. Comparing a 41-year model hindcast with decades of wave measurements from the Baltic Sea. Ocean Engineering, 152, 57–71. https://doi.org/10.1016/j.oceaneng
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 days ago
of Computational Biology (ICB) , as part of the Computational Health Center at Helmholtz Munich, is globally recognised for innovations in data analysis and modelling of biological systems and diseases, anchored
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cooling approaches. As the successful candidate you will also contribute directly to the engineering development and validation programme, bringing hands-on capability in 3D CAD and CFD modelling to support
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Infrastructure? No Offer Description The Centre for Lithospheric Research (https://clr.geology.cz/ ) was established in 2012 within the Czech Geological Survey on the basis of an initiative by the Czech government