82 molecular-modeling-or-molecular-dynamic-simulation PhD positions at Technical University of Denmark in Denmark
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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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Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience
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tasks will be to: Develop and implement machine learning models for dynamic simulations of renewable power systems Develop comprehensive guidelines for verifying and testing dynamic equivalents Integrate
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and kinetic modelling Expression, purification, and characterization of enzymes from fungal and bacterial sources Development and optimization of enzyme assays Structure–function studies of enzymes
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molecular interactions between ICB and γδ T cells. Position 2 will focus on the potential role of γδ T cells in immune related adverse effects (irAEs). Both positions will be in close collaboration with
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industrial processes. Your research will drive a paradigm shift in how TES systems are modelled, integrated, and controlled within industrial settings. You will develop novel, adaptive, physics-informed models
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background in experimental microbiology and has laboratory experience in e.g., minimum inhibitory concentration (MIC) assays, molecular techniques (qPCR and dPCR), and fluorescence microscopy. You are expected
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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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background in Intelligence, Security, or a similar degree with an academic level equivalent to a two-year master's degree and with an interest (and ideally some experience) in Agent-based Modelling, Simulation
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Job Description AI has begun to transform molecular discovery and design for proteins, DNA, RNA, small molecules and more. Yet many outstanding challenges in health and sustainability remain data