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- Fondazione Bruno Kessler
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of the proposed PhD are: (i) To investigate novel neural scene representation methods and their complementary with respect to conventional geometric methods (ii) To develop methods to decompose raw 3D scenes
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look for correlations between transient phenomena in the ionosphere and seismic events. The successful candidate will develop and apply state-of-the-art machine learning techniques to enhance
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health by advancing EU soil monitoring and indicator development. The candidate will also develop methods to assess and report the evolution of soil health against the Soil Mission specific objectives
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) to develop new approaches for 1) advanced acquisition routines for STEM, 2) imaging of beam sensitive materials, including 2D materials, 3) analysis of materials for optoelectronics, such as semiconductor
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the use of formal monitors and safety cages to provide dependability guarantees for components using AI. By building on state-of-the-art tools like OCRA and xSAP, the goal is to develop a robust MBSE flow
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the structural and electronic properties of complex materials. Using first-principles simulations, machine learning techniques, and advanced Monte Carlo methods, the student will develop predictive
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to develop advanced methods for artifact-free hemodynamic angiography with applications primarily in ophthalmology, but also in neuroscience and cancer research. Where to apply E-mail [email protected]
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responsive materials for tethered robotic function is part of the second endoscopic area namely the olfactory clefts. The goal of the PhD is to develop 3D-printable light responsive materials based on Liquid