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machine learning models that predict soil health and crop performance. The position will exploit datasets integrating biochemical and molecular soil parameters (with a focus on microbiome features from
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resonance imaging) Fluency in English Experience and knowledge: Required: Experience in computer programming Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow
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resonance imaging) Fluency in English Experience and knowledge: Required: Experience in computer programming Expertise in Python programming for Machine and Deep Learning, e.g., sklearn, pytorch, tensorflow
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parameter estimation Knowledge of advanced Bayesian methods and samplers, machine learning approaches to signal processing; additionally other methods such as simulation-based inference Good computing skills
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or pre-printed at least one primary research paper as first or co-first author You have some experience in experimental work Desirable but not required/ Nice to have A strong foundation in machine learning
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research paper as first or co-first author You have some experience in experimental work Desirable but not required/ Nice to have A strong foundation in machine learning and statistics You are experienced
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, computer science, bioengineering, data science, or a closely related discipline. • Demonstrate advanced proficiency in artificial intelligence and machine learning, particularly in applications involving
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environments, specifically Computer Vision, Machine learning algorithms and methods for rock characterization, fragmentation prediction, and mining optimization. Specific Requirements Good academic and
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atmospheres and detectability studies Model development of 3D stellar atmospheres Applications of machine learning and AI to exoplanet data analysis Biomarkers and habitability of Earth-like planets Where
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quality alarm protocols based on machine learning: thresholds, alert workflows, and response or shutdown measur. Analyze data (time series) and develop quality indicators to support municipal decision