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available in the field Sufficient scientific and methodological hindsight to understand the level of relevance of research approaches and to be able to combine them in an astute way in the analysis
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partners. Qualifications Ph.D. in Computer Science, Applied Mathematics, or a related field. Strong publication record in machine learning, with preference for expertise in representation learning, deep
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and avoid indirect land use emissions from the clearing of new forests. Requirements Programming skills, preferably in Fortran, Python / R Knowledge of remote sensing data processing and analysis
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on multiple components by analyzing maintenance data, performing failure analysis and giving recommendations backed by laboratory testing and emulation results. The candidate must be comfortable with operating
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soil moisture Participate in field data collection and data analysis Satellite images processing Publish research findings in peer-reviewed journals and present results at conferences and workshops
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of artificial intelligence (AI) into real-time data analysis. This integration can revolutionize the interpretation of remote sensing data, allowing for rapid decision-making in critical situations, such as
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computer programming tools such as Matlab and/or Python. Knowledge of statistics and mathematical modeling. Experience in large spatial data processing, analysis, and interpretation. Experience in running