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/ computer vision and pattern recognition, including but not limited to biomedical applications Strong interest in applied machine learning, including but not limited to deep learning Experience utilising GPU
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to real-world error patterns by means of learning methods. This requires a recognition of the diverse and complex error patterns that can occur in quantum devices in real-world scenarios. To achieve
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between radiative, climatic, and morphological processes. The DITEN laboratory of UniGe brings complementary expertise in signal processing, remote sensing, pattern recognition, and energy systems
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