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situated in the field of machine learning. Potential research topics include, but are not limited to, algorithmic knowledge discovery, graph mining and social network analysis, optimization for machine
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to the human nervous system. You will work closely with Prof. Svein Kleiven, Assist. Prof. Zhou Zhou, and Assoc. Prof. Xiaogai Li at the Neuronic division, and will also collaborate with other research groups
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to extract knowledge from data, modelling large-scale complex systems, and exploring new application areas in data science. Areas of interest include but are not limited to models and algorithms for knowledge
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implement in-situ sensors (3D scanner, thermal imaging, visual camera, etc.) and adaptive toolpath strategies to assist hybrid manufacturing. develop digitally driven value chain models to estimate
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at KTH Royal Institute of Technology is seeking a highly motivated doctoral student with a strong background and interest in spatial AI, navigation, sensor fusion, optimal estimation, and machine learning
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strong background in computer science, including formal methods and mathematics, as well as an interest in AI and safety-critical systems. Good programming skills are required. Supervision: Prof. Elena
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Laboratory in Solna in Stockholm, Sweden(https://www.scilifelab.se ), a national centre for molecular biosciences with focus on health and environmental research Supervision: Prof. Emma Lundberg and Dr. Diana
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in Stockholm, Sweden. The successful candidate will join the research group of Prof. Josefin Larsson and conduct research on supernova remnants. The position focuses on the analysis and interpretation
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at the Division of Communication Systems under the supervision of Prof. Cicek Cavdar and Prof. Emil Björnson. The results will be published in top-level journals and prepare you for a research career in academia
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computing, networked systems, and beyond. The work will range from theoretical and algorithmic development of distributed protocols and coordination mechanisms, through the design and implementation