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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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set of sensors (LiDAR, RGB, IR, and Spectrometer) that enable advanced plant measurements, that allow us to assess plant’s water budget in response to abiotic stress and nutrients’ application
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, the next step in this project is to address sparse optimization for tensors. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing
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stress. Responsibilities: Monitoring PV panels: temperature, efficiency, dust accumulation. Using environmental sensors and thermal cameras (UAV/IR). Comparative analysis of PV configurations: with vs
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) to predictive maintenance challenges. Develop and fine-tune LLMs to analyze and interpret unstructured data (e.g., maintenance logs, sensor data, technical reports) for predictive insights Collaborate with domain
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algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be on creating and optimizing state-of-charge (SOC) and state-of-health (SOH
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such as air quality monitoring, water leak detection and energy monitoring of electric vehicle batteries. The candidate will need to master sensor technologies, embedded systems, and communication protocols
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and sustainable sensor systems for industrial applications. This position offers an exciting opportunity to contribute to cutting-edge research in the field of sustainable materials to develop promising
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interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific computing and machine learning. The research will emphasize both theoretical
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multisource data (IoT, sensors, satellite images, social media, administrative data). Understanding of urban planning issues (urban forms, basic services, sustainability, resilience). Personal and