114 web-development-"https:"-"https:"-"https:"-"Fraunhofer-Gesellschaft" PhD positions in Norway
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invites applications for a PhD position focused on developing a theoretical framework for monitoring and updating adaptive learning systems (including machine learning/artificial intelligence systems) under
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herbivores space use behavior in relation to snow conditions, data is required at cm to m resolution. This PhD project will develop and apply remote sensing methods to advance terrestrial snow monitoring
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focus is resilience and security, developing strategies and metrics to maintain dependable operation under failures, noise, and adversarial conditions, including measures such as QBER and detectability
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contribute to the development of sustainable and data-driven manufacturing systems and will be conducted in collaboration with industrial partners and international research networks. Duties of the position
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of Marine Technology , as part of the Norwegian Maritime AI Center (MAI) at NTNU . As a PhD candidate, you will conduct research to develop AI-driven methods for efficient methods for simulation-based testing
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to knowledge development, education, and enlightenment that promote sustainable, fair, and knowledge-based societal development. Committed colleagues in a good working environment. Good welfare schemes
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by developing innovative non-destructive evaluation techniques and advanced digital tools for diagnostics, conservation and public engagement. Your immediate leader will be the Head of the Colorlab
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, or development studies. Admission requirements (1) To be admitted to the PhD Programme in Educational Sciences for Teacher Education, the applicant must normally have completed a five-year master’s degree
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shipbuilding industry and develop frameworks and knowledge of AI-enhanced planning in shipbuilding supply chains. Apply quantitative methodologies, such as simulation, analytical modelling, and AI‑driven
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magnets, unconventional magnetic systems, and topological materials. The candidate will develop and apply advanced computational techniques, including (TD)DFT and post-DFT analyses, alongside spin dynamics