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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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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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Sabina in the provincial world, especially on the eastern side. It is based on the comparison between their images (including private portraits resembling Hadrian and Sabina), on different media, mainly
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collaborator specialized in “data management”. The planned activities include: - management of a registry collecting clinical, genetic, and imaging data from patients affected by genetically determined
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for the realistic simulation of space images. The work lies at the intersection of computer graphics, space engineering, and autonomous GNC systems, addressing the image rendering needs for lunar landing, in-orbit
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-reality platform for medicine: interactive 3D models are reconstructed from 2D images (e.g., DICOM) and rendered on AR devices such as HoloLens 2 via Unity. Clinicians can manipulate the models and perform
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for strengthening activities in relation to their specific expertise (e.g., computational imaging, deep learning, numerical optimization) Where to apply Website https://concorsi.unige.it/home Requirements Additional
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performance in terms of sensitivity, stability, and robustness to motion artifacts. The resulting smart eyewear prototype will enable real-time, privacy-preserving facial expression recognition with potential
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-ERIC project “LEMIS” (Analysis and imaging of Light Elements in Materials of Importance to energy Storage using ion beams). The position will remain open until filled. The position is available
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, multi-agent platform for the analysis and simulation of complex data. It involves creating clinically interpretable virtual patient models by integrating diverse data types, including radiological imaging