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the suitability and potential benefits of LLMs (and other machine learning models) in these tasks. These investigations include the feasibility, practicality and success evaluation of prototype implementations
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for using AI to develop social engineering attempts. This project combines human subject research of learning and decision making, Human-Computer Interaction, and the advancement in AI methods
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looking for a full-time (100%) doctoral scholarship holder in the field of machine learning for circular polyurethane design. Position You will actively work on the preparation and defence of a PhD thesis
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Economics » Environmental economics Engineering » Industrial engineering Environmental science » Ecology Technology » Environmental technology Computer science » Informatics Engineering » Process engineering
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of reinforcement learning (RL) for industrial process control and optimisation. The research focuses on developing RL methods that can support decision-making and control in complex industrial systems while
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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
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, MATLAB, C/C++, etc.) and/or knowledge of holographic imaging is a plus; Prior knowledge and hands-on experience with state-of-the-art machine learning frameworks (e.g., sci-kit-learn, Tensorflow, PyTorch
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actively on the preparation and defence of a PhD thesis in the field of explainable reinforcement learning (XRL). Explainable reinforcement learning aims to make decisions, policies, and learning processes
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and cooperation. You have a strong interest in machine learning/artificial intelligence. You have experience with deep learning. You have experience with reinforcement learning (preferred). You have
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and cooperation. You have a strong interest in machine learning/artificial intelligence. You have a strong interest in graph-based learning (e.g., graph neural networks). You have experience with deep