3 machine-learning-"https:"-"https:"-"https:"-"https:"-"RAEGE-Az" positions at Università degli Studi di Genova in Italy
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of physics- informed machine learning and deep learning, with applications to inverse problems in scientific imaging and the modeling of complex physical systems. The overall goal is to integrate the knowledge
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fluorescence microscopy (SMLM, SIM), integrating physical-mathematical models, machine learning, and compressed sensing for accurate and efficient reconstructions. Applicants must submit a project implementing
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scientific imaging (TR-FLIM, HSI, ISM), designing mathematical and unsupervised learning algorithms for nonlinear inverse problems, with reliable reconstructions even with limited data. Where to apply Website
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