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Job Description DTU, Department of Civil and Mechanical Engineering, the Section for Manufacturing Engineering invites applications for a PhD position (3 years) on the topic of simulation of process
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) technology with innovative biomaterial systems and cell therapy approaches. The successful candidate will join a dynamic research team with extensive expertise in RNA biology, drug delivery, and translational
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systems, and husbandry practices. This Ph.D. position aims to gain new knowledge on fish microbiome-health & welfare dynamics, the development, stability, and resilience of microbiomes and performance and
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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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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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renewable power system dynamics. Collaborate with experts from DTU and IIT Bombay, gain hands-on experience with advanced simulation tools, and contribute to high-impact publications. Enhance your
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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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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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) 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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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