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analytics. The research assistant will develop real-time flight control algorithms, AI- based data processing, and mission management platforms, contributing to the deployment of smart UAV demonstrators under
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computing, and digital twin technologies for mission autonomy and predictive analytics. The research assistant will develop real-time flight control algorithms, AI- based data processing, and mission
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sensors, actuators, control algorithms, and embedded systems. Guide the development and deployment of digital twins for real-world processes and infrastructures (e.g., factories, greenhouses, robotics
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teams in the design and implementation of cyber-physical systems (CPS) integrating sensors, actuators, control algorithms, and embedded systems. Guide the development and deployment of digital twins
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) integrating sensors, actuators, control algorithms, and embedded systems. Guide the development and deployment of digital twins for real-world processes and infrastructures (e.g., factories, greenhouses
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conferences and journals. Overview: The successful candidate will join an interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific
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optimization of dynamic, uncertain, and multiscale systems. Guide the design and implementation of numerical algorithms, optimization routines, and simulation-based decision tools. Support project-based learning
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component. The battery management system (BMS) unit is not just a component, but a crucial element tasked with monitoring each cell of the battery and running algorithms to calculate state of charge (SoC
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to analyze and interpret unstructured data (e.g., maintenance logs, sensor data, technical reports) for predictive insights Collaborate with domain experts to integrate LLM-based solutions into predictive
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close-to-field conditions, and (ii) a fully autonomous phenotyping robot, Phenomobile.v2+, equipped with a set of sensors (LiDAR, RGB, IR, and Spectrometer) that enable advanced plant measurements