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of the academic staff within CVL. What are we looking for? You are highly motivated, self-driven, and curious to advance use-inspired artificial intelligence methods. You bring along your enthusiasm
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from oil spills and extraction remain a major concern, requiring effective strategies to reduce both immediate and long-term impact. Conventional remediation methods, such as skimming, in-situ burning
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to reduce both immediate and long-term impact. Conventional remediation methods, such as skimming, in-situ burning and dispersants, are well proven over the decades and provide scenario-specific mitigation
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methods to track learning curves and quantify operator skill progression over repeated tasks, identifying points where adaptive haptic guidance can be most effective. At the same time, insights from expert
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spray drying are typically reliant on trial-and-error workflows, a narrow selection of polymers, and analytical methods that are unsuitable for early-stage screening due to high material demands. Moreover
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reliant on trial-and-error workflows, a narrow selection of polymers, and analytical methods that are unsuitable for early-stage screening due to high material demands. Moreover, no reliable predictive