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Field
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. • Karimi H. et al., “Wavelet Based Protection of Microgrids”, IEEE Transactions on Smart Grid, 2019. • Heidari A. et al., “Deep Learning for Fault Detection in Smart Grids”, Applied Energy, 2021. • Wen L. et
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contain well-informed methodological considerations. To find out more about the department please go to https://www.cbs.dk/si. ; A particular quality of the department is in the use of empirical
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, computational physics, or a related field; • Strong background in machine learning, probability, and statistics; • Proficiency in scientific programming with Python and deep-learning frameworks such as PyTorch
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Development of machine and deep learning methods
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, the ability to analyze the full dataset collected by the experiment will be severely limited. The L2IT is a leader in developing new track reconstruction algorithms using geometric deep learning methods
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doctoral programme in Technology within three months of starting in the position. (https://www.usn.no/english/research/postgraduate-studies-phd/our-phd-programmes/technology/). The doctoral programme
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analog, requiring the model to integrate multimodal inputs to anticipate the onset and spatial evolution of ionospheric storms. The successful candidate will work at the intersection of deep learning and
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, Python or similar) Specific Requirements Interest in optical imaging and interferometry. Prior knowledge will be a plus Interest in computational methods, image processing and machine/deep learning. Prior
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). Desirable assets are: • Machine learning, deep-learning, artificial intelligence, advanced statistical inference; • A solid record of research activities, including relevant publications in international peer
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% of your time), including tutorials and supervision of Bachelor’s theses. This is what we ask of you This is an interdisciplinary project that combines machine learning and AI, probabilistic risk