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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | 25 days ago
collaboration with L. Bonati at IIT Genova, who developed the library mlcolvar, https://github.com/luigibonati/mlcolvar ). 2) Compare the data-science dimensional reduction approaches above, with machine learning
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We are seeking creative and energetic candidates with strong experience in multimodal machine learning and human behavior analysis and modeling for a one-year Postdoctoral position. Using recent
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the leadership of Principal Investigator Dr Andrew Siemion. Listen's interdisciplinary research has synergies with many of the department's research priorities, including exoplanet studies, machine learning
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and machine learning. Knowledge of the basics of federated learning and causal inference is highly encouraged. Proven track record in research and development of machine learning algorithms. Proficiency
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of computational methods that enable machines to perform tasks requiring perception, learning, reasoning, and decision-making. It encompasses core areas such as machine learning, data-driven modeling, intelligent
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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. 3. Machine Learning and Predictive Analytics: • Develop and apply machine learning models (including Azure Machine Learning) to optimize healthcare data analysis accuracy. • Collaborate with data
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theory, Machine learning and multivariate statistics, Application in neuroscience, climate research, economics, ...). COBRA is a part of the Department of Complex Systems of the Institute
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problems, statistical learning and machine learning (machine learning, deep learning) - Knowledge of associated software development tools and environments: Python, PyTorch, Scikit-learn, Jax, Julia
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Knowledge, Skills, and Abilities: Hands-on experience performing FEFF calculations and data preprocessing for machine learning applications. Practical experience developing and training models using PyTorch