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analytical in your approach. You have good computer skills; experience with image analysis, programming or statistics is an advantage. Regarding the role of study volunteer and patient contact: you have a good
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modeling of cell morphology and tissue function using imaging and computer vision; AI models of disease and digital twin applications. Biological applications and disease areas ideally focus on genetics and
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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
spatial multi-omics data; AI-based modeling of protein structure and protein interaction networks; AI-based modeling of cell morphology and tissue function using imaging and computer vision; AI models
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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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gained to improve the sustainability of agriculture and the climate change resilience of crops. We are currently looking for an expert in Computer Vision, Image Analysis and AI to join our team. In
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, and healthcare AI. You will contribute to the management of the research group and to the further development of the research agenda around the ERC Consolidator Grant IONIAN (https://erc
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-computer interfaces, audio signals for keyword spotting and artificial cochleas, and tactile signals for robot perception. Various types of bio-inspired mechanisms have been investigated in recent years
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offering state-of-the-art study programmes grounded in research in a wide range of academic fields, Ghent University is a logical choice for its staff and students. The "WAVES" research group (http
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the running infrastructures. Using cutting-edge computer vision, wearable sensors, and citizen science, RUN2GETHER will capture large-scale, real-world data during running events and group runs. These data will
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cutting-edge computer vision, wearable sensors, and citizen science, RUN2GETHER will capture large-scale, real-world data during running events and group runs. These data will advance our understanding