799 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" Postdoctoral positions
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Polytechnique de Paris. The group conducts research at the intersection of statistical learning, machine learning, and data science, with a strong focus on structured data, representation learning, and
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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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based on neutral atom platforms, exploring both theoretical and experimental domains. Research will span quantum control, quantum-enhanced machine learning, and hybrid quantum-classical computation
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Experience in machine learning, math, and programming. LanguagesENGLISHLevelGood Additional Information Work Location(s) Number of offers available1Company/InstituteUniverCountryBrazilState
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testing and collaboration with infrastructure owners or managers - Experience in supervision - Knowledge of data-driven methods, signal processing, or machine learning - Familiarity with sustainable
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 21 hours ago
and related activities. Strong programming skills are a must, including experience with machine learning. Good written and oral communication skills in English are important. Point of Contact Mikeala
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-off companies. CONTEXT AND MISSION We are seeking a postdoc to join the Quantum Machine Learning team (QML-CVC) in beautiful Barcelona. The QML-CVC team (https://qml.cvc.uab.es /) is part of
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infrastructure (e.g. Observatorio del Roque de los Muchachos) Hands-on training in cutting-edge techniques, from detector R&D to advanced data analysis and machine learning. Attendance to international
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development opportunities, including a membership to Academic Impressions, LinkedIn Learning, and UT Dallas Bright Leaders Program. Visit https://hr.utdallas.edu/employees/benefits/ for more information
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Responsibilities will vary depending on the Fellow’s background, but may include: Developing machine learning, optimization, or simulation models to improve clinical operations and resource allocation Advancing