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-of-the-art by exploring novel experimental and algorithmic approaches enabling spectroscopy and imaging of quantum materials and biological samples with extreme spatial and temporal resolution. The work at the
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Learning algorithms (clustering algorithms (K-means), genetic algorithms, and reinforcement learning) and end-user piloting of software systems – including technical attributes and legal/commercial
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in underground facilities. The project aims to evaluate sensor technologies, design and optimize multi-sensor monitoring networks, and develop advanced detection and localization algorithms adapted
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/26. Preferred Qualifications: Strong background in algorithms, human-computer interaction (HCI), and software engineering. Experience in robotics systems, interactive or intelligent systems, or AI
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is to design a data architecture capable of harmonising sensor data and integrating them with artificial intelligence algorithms for predictive irrigation management. The research will include
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reducing waste, product failures and emissions. For this master’s thesis you will join our Competence Unit Complex Dynamical Systems , which focuses on the development and deployment of algorithms to control
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, design and optimize multi-sensor monitoring networks, and develop advanced detection and localization algorithms adapted to complex 3D underground geometries. The research will be conducted in close
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Anomaly detection is an important task in data mining. Traditionally most of the anomaly detection algorithms have been designed for ‘static’ datasets, in which all the observations are available
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conditions de restauration dans un problème inverse avec contrainte de parcimonie, et de proposer des algorithmes utilisant ces conditions [1]. Ce sujet de thèse étudie le problème dans le cadre de
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algorithms with surgical robotics. The RA will design and implement cutting-edge algorithms, and also be actively involved in the development AI tools tailored for different medical domains. These are efforts