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and analysis of experimental data; Take the lead on writing of research reports and communicating the scientific results for conferences and scientific publications Participate in the training and
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unstructured data (e.g., maintenance logs, sensor data, technical reports) for predictive insights Collaborate with domain experts to integrate LLM-based solutions into predictive maintenance workflows. Explore
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approaches for approximating CFD results Analyze and interpret data from scale-down and scale-up experiments Publish scientific results in peer-reviewed journals in a timely manner Present research results
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data sequences from the project and reports. Prepare high draft quality manuscripts for submission Mentor master students and PhDs Education, qualifications, and experience Applicants must have earned a
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parameters to optimize recovery and product quality; Evaluate potential valorization routes for process by-products and residues; Analyze, interpret, and synthesize experimental data to support process
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high-impact journals Contribute to data visualization platforms Required Qualifications Ph.D. in Atmospheric Science, Environmental Science, Remote Sensing, or related field Experience in atmospheric
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generate data that will be used to develop new models of the dissolution and diffusion of different fertilizer formulations. The main responsibilities are: Conduct experiments in the Lab, prepare soil
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, while integrating real-time data into cloud platforms to develop reliable, secure, and scalable solutions. Main tasks and responsibilities Design, develop, and test IoT solutions for air quality
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. without vegetation. Studying dust deposition and its impact on energy performance. Analyzing meteorological, soil, and energy production data. Contributing to the modeling of PV performance under local
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Ability to transform complex data into actionable insights for research and decision-making. Strong capacity to work within multidisciplinary teams, including urban planners, technologists, and hydrology