30 software-defined-networking-"IMEC" PhD positions at Technical University of Denmark
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. Opportunities to participate in conferences, symposia, and networking events to share and enhance your research. Your role will be pivotal in driving AI innovation and contributing to a transformative approach to
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loads — EV fleets, residential batteries, smart heat pumps, and data-center clusters — across distribution and transmission networks is critical to unlocking deep decarbonization and maintaining grid
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Development/upgrading solid oxide cell test setups for advanced electrochemical characterisation, including development of metal test houses Development of dedicated circuitry and analysis software
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customization of Large Language Models for educational purposes. The ideal candidate must have a strong professional network and documented collaboration capabilities, alongside a proven track record in
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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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horizons for advanced technologies. Responsibilities and qualifications The PhD project will focus on the design, synthesis, and characterization of new types of metal-organic network structures, which
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modelling or coupled wind-wave modelling Experience with wind resource assessment and site suitability, including WAsP and WEng software Experience using wind turbine wake models Knowledge of meteorological
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large national and international network and cooperate with research partners, public authorities, industry, and NGOs. We have state-of-the-art research facilities and Denmark’s only ocean- and arctic
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, secure digital communication, medical technology, and new analytical methods. We use and develop basic theory, next-generation instrumentation, and software, and aim to make our data publicly accessible
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. Variational Autoencoders, Normalized Flows, Generative Adversarial Networks) Have experience in developing fast algorithms for hard combinatorial optimisation problems. Have some knowledge about stochastic