67 postdoc-molecular-dynamics-simulation PhD positions at Technical University of Denmark in Denmark
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materials built by covalent linking of monomers, supramolecular polymers are dynamic and formed by the self-assembly of monomeric units brought together by non-covalent interactions. The connections between
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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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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
feedback, and real-time agent-based simulation for guiding optimal work performance. Following smart serious gaming approaches, novel artificial intelligence forecasts human behavior and provides active
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holistic multi-hazard risk framework capturing cascading effects across systems and scales; (2) the creation of digital environments utilizing real-time data for dynamic risk evaluation; (3) the advancement
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to apply machine learning techniques to a combination of experimental data and simulation results, aiming for faster and more accurate predictions. About us You will join an international and highly
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) the development of a holistic multi-hazard risk framework capturing cascading effects across systems and scales; (2) the creation of digital environments utilizing real-time data for dynamic risk evaluation; (3
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an extrusion machine that produces large-scale earth blocks Building a 3D printer that utilizes earth materials for construction purposes Developing numerical process models that simulate 3D earth printing
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with researchers at DTU and KTH, you will help develop an integrated decision-support system that: Uses real-time sensor data and AI models to assess risk scenarios. Dynamically recommends optimal
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of digital environments utilizing real-time data for dynamic risk evaluation; (3) the advancement of risk-to-resilience methodologies; and (4) the establishment of digital twin-based resilience frameworks
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that merge thermo-fluid dynamic laws, deep learning, and experimental data. A central goal is to overcome current limitations in TES operation and optimization, enabling discovery of new high-performance and