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specified timelines. Ability to prioritize tasks, set milestones, and monitor progress. Continuous Learning and improvement: Willingness to stay updated with the latest advancements in road condition research
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). The emergence of data-driven techniques (broadly grouped under the term “machine learning”) challenges the traditional foundations of controls and represents an alternative paradigm that cannot be ignored
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, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race
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, Astronomy, or a closely related field is required. Experience with HPC systems, machine learning, and GRB monitor data analysis would be an advantage. Additional Information Applications must be submitted
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the Danish Ministry of Foreign Affairs and managed by Danida Fellowship Council. Ethio-Nature aims to optimize the use of machine learning and remote sensing to site nature-based solutions that enhance local
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thermomechanical process simulations such as casting and welding. The research activities at SDU-ME spans widely from fluid mechanics, condition monitoring, machine learning, fatigue, maritime structures
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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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Institute (https://cse.umn.edu/aiclimate). The role involves building knowledge-guided machine learning (KGML) models for sustainable agricultural practices, developing AI-ready benchmark datasets, and
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rise (SLR) and flooding. Integrate field data (e.g., salinity, nutrient levels, soil and water properties) into the development of numerical models to enhance predictive accuracy. Apply machine learning
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 2 months ago
research using various statistical and machine learning approaches to develop regional and global products and improve our understanding of the drivers of carbon stock changes across a variety of ecosystems