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maintenance systems using AI tools. Key Responsibilities: Conduct innovative research on the application of Large Language Models (LLMs) to predictive maintenance challenges. Develop and fine-tune LLMs
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. The candidate will apply their expertise to advance predictive maintenance systems using AI tools. Key Responsibilities: Conduct innovative research on the application of Large Language Models (LLMs
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Design and execute experiments to study molecular and physiological processes in plants. Utilize tools such as proteomics, and metabolomics. Analyze plant phenotypes under controlled and stress conditions
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to dissect regulatory networks in model and/or crop plants. Key Responsibilities Design and execute experiments to study molecular and physiological processes in plants. Utilize tools such as proteomics, and
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) to monitor and improve public health. You will contribute to modeling smart cities with a focus on health and designing decision-support tools for sustainable and inclusive urban environments. Key
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transformer-based architectures to create a powerful tool for understanding and predicting bacterial genomic sequences. The successful candidate will play a key role in developing and optimizing these models
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working on projects aimed at developing innovative, accurate, and cost-effective tools for foliar analysis and diagnosis. These tools will leverage various spectroscopic techniques (VNIR, SWIR, and XRF
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tools, data science techniques, and spatial analysis to leverage big data from cities and model their evolution. Main Tasks and Responsibilities: Collect, clean, and structure large volumes of urban
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developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning of continental surfaces and their interaction with climate and
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position in Plant Spectroscopy. The selected candidate will join an interdisciplinary team working on projects aimed at developing innovative, accurate, and cost-effective tools for foliar analysis and