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junior and senior scientists collaborate, each with their expertise, to carry out a scientific activity with a shared research goal. The Electron Spectroscopy and Nanoscopy Research unit is coordinated by
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29 Aug 2026 Job Information Organisation/Company Università degli Studi di Pavia Research Field Engineering Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 9 Sep 2026 - 12:00...
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2 Sep 2026 Job Information Organisation/Company Università degli Studi di Brescia Research Field Engineering » Electronic engineering Researcher Profile Recognised Researcher (R2) Leading Researcher
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21 Aug 2026 Job Information Organisation/Company Gran Sasso Science Institute Research Field Engineering » Electronic engineering Engineering » Aerospace engineering Physics » Other Researcher
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integrating AI with vision at the edge. Despite recent advancements, the synergy between AI and computer vision remains constrained by fundamental imaging bottlenecks. Conventional HDR techniques frequently
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proficiency in coding, knowledge of GIS environments and point cloud processing, strong interest in heritage scenarios as well as a collaborative attitude for interdisciplinary work between computer scientists
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on ultrafast chirality and attosecond electron dynamics, aiming to develop new methods for probing and controlling chiral light–matter interactions with applications in photonics, biosensing, and materials
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cities. Besides the requirements established by the rules of the IECS school, preferential characteristics for candidates for this scholarship are: – Master degree in Computer/Data Science, Mathematics
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a strong background in artificial intelligence and 3D computer vision, with solid programming skills and an interest in 3D data processing (e.g. point clouds and neural scene representations), along
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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