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in the design and implementation of network solutions. You have strong mathematical skills in the analysis of network systems. Working experience with robotic systems and AI/ML is considered a plus
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collaboration between NLP researchers at the UGent - IDLab Text-to-Knowledge research cluster, researchers on social robotics at UGent - IDLab, and researchers on emotion recognition at UGent - LT3. Perform your
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for analysis of network systems. Working experience with robotic systems and AI/ML is considered a plus. You are proficient in one or more programming languages (C++, Python, Java, …) and eager to further
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application areas are Mechatronic systems, Industrial robots and Industrial processes. We are part of the department of Electromechanical, Systems and Metal Engineering (EMSME) within the Faculty of Engineering
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conversational AI models, based on recent foundation models, and in a multi-modal context, i.e., targeting use cases in human-robot interactions. The key research question is how state-of-the-art language models
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conversational AI models, based on recent foundation models, and in a multi-modal context, i.e., targeting use cases in human-robot interactions. The key research question is how state-of-the-art language models
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Job description PhD Researcher in Adaptive Deep Neural Networks for Robotic Sensing The IDLab Ghent research group is seeking a highly motivated and talented PhD student to join the distributed
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skills in the analysis of network systems. Working experience with robotic systems and AI/ML is considered a plus. You are proficient in one or more programming languages (C++, Python, Java, …) and eager
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distributed machine learning team. Our team focuses on developing efficient machine learning algorithms for perception and control; with diverse applications in industry, robotics, remote sensing and