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Field
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At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in
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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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for a research associate position on the topic of deep learning for particle physics.The Cluster of Excellence “Quantum Universe” performs research to understand mass and gravity at the interface between
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heating and cooling, storage, and local electricity grids. A key goal is to translate methodological innovations in deep learning into practical tools for sustainable urban energy systems, supporting
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from renewable electricity and sustainable raw materials, represent a promising solution, enabling deep decarbonization. DESIRE is a Marie Sklodowska-Curie doctoral network that aims to train 15 doctoral
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learning, image analysis, and advanced computing to study relationships between structure and function. Keywords: Human Brain, 3D Atlas, Deep Learning, Temporal Lobe, Brain Function Entry Requirements
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of the bioprinting process. Objective 2: Training of a deep learning model to predict inputs that will achieve bioprinted scaffolds with the required print fidelity and scaffold micro-architecture. Objective 3
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into the generation process. This multidisciplinary project will deliver deployable models, reproducible methods, and, where allowed, shareable datasets. The student will gain training in deep learning, AI, image
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at the intersection of AI and advanced electron microscopy. The project focuses on developing novel self-supervised and physics-informed deep learning methods to restore and denoise Transmission
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processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job