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machine learning by designing and developing innovative models and algorithms. Key Responsibilities: Designing and conducting comprehensive research in artificial intelligence and machine learning, with a
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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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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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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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: algorithm design for the interpretation of measurements, designing algorithms for deciding which experiments to perform, communicating with the instruments, orchestrating the steps of the research campaign
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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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learning, algorithms, and programming. Prior exposure to reinforcement learning or human-robot interaction is highly desirable, though motivated candidates with a strong grounding in AI/ML and willingness
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-aware AI, HR analytics and logistics, optimisation techniques for labour and warehouse management. Experience of applying Machine Learning algorithms (clustering algorithms (K-means), genetic algorithms
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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