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background in Computer Science, Informatics Engineering, Mathematical Modeling, Computational Urban Science, Transport Modeling or equivalent, or a similar degree with an academic level equivalent to a two
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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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are meteorology, mesoscale modelling, analysis and interpretation of meteorological datasets. We are also interested in hearing from researchers with oceanographic, as well as meteorological, science background
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an efficient AI foundational exploration of the molecular space. How can we bias the generative models towards desirable molecular properties How can we integrate generative AI models and different molecular
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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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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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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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. 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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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