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an experimental team, with direct availability of experimental validation for machine learning models. Competitive salary and full benefits. Access to state-of-the-art computing infrastructure. Fully funded for 4
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing. UConn has a vibrant
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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collaborators The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 13 hours ago
differential equations # Knowledge of Scientific computing / high-performance computing # Knowledge of Algorithmic modeling and simulation # Fundamentals of machine learning or quantum computing # Programming
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Learning, or a closely related field. Strong understanding and demonstrated track record in protein structure modelling methods, with hands‑on experience in protein or biologics design and engineering. Hands
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learning models on wearable electronic circuits, devices, and platforms, with particular emphasis on smart eyewear. The research activities will address multiple application domains, including embedded
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Biology Scientist in Single-cell omics & AI to support the valorization trajectory of a computational platform combining single‑cell omics, AI machine learning, and translational biology. The role involves
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collaborations and perform cross-species comparisons. We use machine learning techniques for neural data analysis and computational modelling with a special interest in biologically-inspired deep learning and AI