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carbon capture simulation through advanced modelling tools—CapSim”. This project aims to improve CO2 capture simulation technology by apply state‐of‐the‐art techniques for evaluation of uncertainties in
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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optimization of waste heat harvesting. Your role will be to simulate the heat transfer processes between façade panels and thermoelectric generators, focusing on maximizing waste energy recovery efficiency. You
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Job Description If you are skilled in Unity VR development and passionate about bioinformatics, this internship lets you build interactive molecular simulations, integrate pipelines and create
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integrated circuits for next-generation UOWC technologies. As a participant of the project, you will become part of a team at DTU with expertise in design, simulation, nanofabrication, characterization, and
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flow modelling and simulations Responsibilities and qualifications The nature of these projects suggests that you should have a strong interest in interdisciplinary research, including coupled physical
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research assistants, Postdocs, and academic staff to develop cutting-edge methodologies. The research is cross-disciplinary, combining advanced quantitative analysis, simulation, and systems integration
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digital co-simulation platforms (e.g., Modelica-Python/Simulink) Applying machine learning and data-driven approaches to enhance the operation of district heating substations Participating in course
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capability to model complicated magnetic systems for two reasons. First, all magnetic sources in a simulation interact, leading to computational resources scaling with the number of sources squared – which is
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co-simulation platforms (e.g., TRNSYS-Python) Implement and test AI-enabled smart energy management strategies in real-world settings Conducting in situ measurements, including planning, setting up