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bottlenecks in data and system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models
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failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics
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. Responsibilities The role in AM2PM, an EU funded research project, involves conducting innovative theoretical and experimental research in Building Information Modeling (BIM), Digital Twin Construction (DTC
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key
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deep understanding of techno-economic evaluation and proven capabilities in the evaluation and modeling of resource recovery and valorization pathways. The role also requires experience in process and
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Job Description RISC-V open source and open standards as the nucleus for new platform models help to improve overall flexibility and productivity for a wide market access. Given the challenge
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modelling approaches will also be used to complement the experimental work. The bioprocess engineering team at DTU Chemical Engineering consists of around 10 scientists and engineers. Expertise is available
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privacy guarantees. This PhD project will develop scalable, privacy-preserving coordination models that jointly optimize DER integration, electrified loads, and data-center flexibility — ensuring fairness
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qualifications around data-driven digital twins, energy systems modelling, forecasting and control. Some prior knowledge on distribution grids and methods for grid services is preferred. Moreover, the following
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model checking. You should be well versed in basic statistics and practical programming skills is a must. Knowledge about the inner workings of GenAI would be nice but not necessary. You must have a two