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holographic information using natural and spatially incoherent light sources. However, the image quality of such systems is still limited by inaccurate models of incoherent light propagation and by the complex
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. While EMT simulation provides the required modelling detail, existing workflows do not scale efficiently to national and regional transmission systems.Our Vision: make EMT-based stability assessment
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advanced experimental and modelling methods to better understand the behaviour of industrial lubricants under extreme operating conditions. Lubricants in gears, bearings and other mechanical systems can be
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staff position within a Research Infrastructure? No Offer Description About DESIRE Climate change and energy security challenges demand a rapid transition from fossil-based energy production
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of reinforcement learning agents understandable to humans, leading to improved transparency, trust, safety, and regulatory compliance in high-stakes decision-making systems. Potential application domains include
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actively on the preparation and defence of a PhD thesis in the field of continual reinforcement learning. Continual reinforcement learning studies how agents can learn across a sequence of changing tasks
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thesis in the field of continual reinforcement learning. Continual reinforcement learning studies how agents can learn across a sequence of changing tasks, environments, or objectives while retaining
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. The work will progress from well-defined model minerals to recycled and secondary mineral resources with the support of the supervisors and project consortium. The position includes the following
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empirically grounded insights into the aesthetic, lived, and institutional realities of contemporary world literature and its agents. Combining textual analysis with sociological and ethnographic methods, EMLIT
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an AI-based image and video processing pipeline dedicated to these novel multi-optics systems. This PhD research is embedded in the project HARMONY_SBO, funded by Flanders Make, the Flemish strategic