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. The candidate will need to master sensor technologies, embedded systems, and communication protocols, while integrating real-time data into cloud platforms to develop reliable, secure, and scalable solutions
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environmental sensors and thermal cameras (UAV/IR). Comparative analysis of PV configurations: with vs. without vegetation. Studying dust deposition and its impact on energy performance. Analyzing meteorological
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(or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs. The candidate will apply
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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
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and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have recently completed (or be close to completing) a PhD in
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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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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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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