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environmental variables to develop LUE, WUE and canopy conductance function for diagnostic mapping of forest ecosystem functioning metrics. We will apply time-series analysis to investigate seasonal and
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. Activities of the successful candidate: Conduct extensive background literature analysis. Plan and organise experiments to define and test hypotheses and develop forefront research. Publish the results
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in a number of the following topics: Turbulence modeling with wave propagation simulations Modulations used in optical wireless communications Data Analysis and Management Implement and open-source
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, and multi-level data analysis Communicate and collaborate with a research team, including teachers and student assistants Engage in international opportunities for learning and development (i.e
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AI agents themselves. The candidate will explore behavioural analysis techniques. Another research questions is related to the definition and application of a unified policy through both legacy IT
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to evaluate. The main research question is how to automatically harmonize the retrieved information allowing a unique analysis and to map them against multiple user-tailored outputs. This is necessary as the
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: · Processing multi- and hyperspectral satellite and drone data · Collection of field data on relevant forest traits and laboratory analysis · Forest radiative transfer modelling · Hybrid
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, or similar languages for data analysis Proficiency in scientific English (written and spoken) is a must, German and/or French is an advantage Willingness to spend several months at other institutions abroad