152 postdoc-in-thermal-network-of-the-physical-building Fellowship positions in Norway
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- University of Oslo
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- NTNU - Norwegian University of Science and Technology
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rated institution of research and education with 26 500 students and 7 200 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important
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referring to statistical and system characteristics in the real world contrary to an ideal learing setting. The candidate will contribute to understanding how neural networks extract the most relevant
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interaction with the world around us – globally, nationally and locally – we shall be instrumental in building a society based on knowledge, skills and attitudes. Do you want to take part in shaping the future
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Fellowship at the University of Oslo. Project description The net uptake of carbon to terrestrial systems (LULUCF) in Norway is estimated to be 20-25 MtCO2e/yr or about 50% of the anthropogenic greenhouse gas
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structured around two main pillars: Network resilience and sovereignty, i.e., research on networking architectures and mechanisms that keep critical networks and applications they support running optimally
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. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You can find more information about working at NTNU and the application process here . ... (Video unable to load
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close interaction with the world around us – globally, nationally and locally – we shall be instrumental in building a society based on knowledge, skills and attitudes. Do you want to take part in shaping
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referring to statistical and system characteristics in the real world contrary to an ideal learing setting. The candidate will contribute to understanding how neural networks extract the most relevant
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to an ideal learing setting. The candidate will contribute to understanding how neural networks extract the most relevant information of the data to make a prediction using advanced mathematical tools
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volumes, there is a plan to utilize modern machine learning strategies like "physics-informed neural networks." One of the main advantages of this approach is that measurements and observations made