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. The successful development of a Digital Twin-enabled IDS will not only improve the cybersecurity of industrial networks but also establish a foundation for further advancements in intelligent, self-learning
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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position is the development of novel machine learning methods for modeling molecular properties, in particular regression models for bi-molecular properties. The research is embedded in the thematic context
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Method (DG) for higher-order temporal discretisation. It is necessary to implement models of various Wells and impulse turbines. The project tasks are: Development of a simulation code in Julia
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Reference Number AE2025-0573 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0573.pdf CALL FOR
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part of the Human-Centered Computing Section (https://www.cs.aau.dk/research/hcc-human-centered-computing ), an ambitious and supportive research environment in which we study the design, development
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on the complementary expertise and recognized excellence of its 22 research teams to contribute to the development of the fundamental aspects of computer science (models, languages, methods, algorithms) and to foster
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applicable law. 3. Work plan: The selected candidate will work out R&D on ML-based Perception for AMRs targeting industrial applications. The work plan comprises the following tasks: - Development of a
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Infrastructure? No Offer Description Are you curious about the mysteries of animal development and eager to uncover how tissues and cells behave in real time? If so, this PhD opportunity could be the perfect fit
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reference. The student will focus primarily on the photonic integration of machine learning methods, contributing equally to the development of ML algorithms in this context. Their work will include