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artificial intelligence—especially deep learning—offers transformative potential for developing next-generation earth system models. Recent breakthroughs, such as neural network-based short-to-medium term
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this limitation in the use of satellite observations by make a direct use of radiance observations retrieved by satellites using machine learning without the need of radiative transfer calculations. The new model
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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, or a related field. Proven experience in machine learning, deep learning, generative AI and data mining. Strong programming skills (e.g., Python, R, MATLAB, or similar). Experience with data
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, Mechanical), Computer Science, Applied Math/Statistics, Physics—or related. Candidates who will graduate in the near future are also welcome to apply. Strong foundation in machine learning/deep learning and
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new knowledge with a clear academic and social impact, in fields such as AI-enhanced translation workflows, Neural machine translation, large language models, or multilingual NLP, Multimodal and
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. The researcher is expected to have (i) strong machine learning skills to improve model performance and robustness, and (ii) exemplary passion and motivation to pursue multidisciplinary research at the intersection
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degree in computer science (or a related field) Rich experience in devising machine learning models, methods, and algorithms for computer vision and image processing. Scientific track record with
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Lab applies rigorous evaluation and modeling methods, including natural and field experiments, randomized controlled trials, behavioral economics, and machine learning, to help policymakers identify and
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, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology. Achieving