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The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
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Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds united in pursuit
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Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds united in pursuit
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Identities, Machine Learning/AI, and IoT/5G on organisations from both the private and public sectors. The group consists of doctoral and post-doctoral researchers from diverse backgrounds united in pursuit
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capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives, including large-scale
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, resilience, and sustainability of stormwater management. The research will focus on integrating AI and machine learning with hydraulic-hydrologic modeling, urban planning strategies, and nature-based
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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integration of model checking and synthesis with machine learning will provide the key to innovative, highly scalable methods for learning, analysis, synthesis and optimization of cyber-physical systems. Based
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Failure Analysis of Composite Sleeves for Surface Permanent Magnet Electrical Machines This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta