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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 1 month ago
training program that promotes cross-disciplinary collaboration and provides in-depth scientific insight as well as a systematic approach to marine data science. For more information, visit: https
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: https://wasp-sweden.org/ The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous
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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
nonlinear optimal control algorithms. Experimentally validating the proposed methods on a waste-sorting robotic platform. Contributing to mechanical and mechatronic design choices whenever they influence
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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high
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machine learning algorithms, the system will be designed to recognize and characterize building activities, occupancy patterns, environmental conditions, and other indicators relevant to the operation of
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the Cortex (https://www.ntnu.edu/kavli/centre-for-algorithms-in-the-cortex) will be funded for 10 years by the Norwegian Research Council. The scientific goal of the Kavli Institute for Systems Neuroscience
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PhD fellowship in fault tolerant quantum algorithms PhD Project in state preparation, observable extraction or noise modelling Niels Bohr Institute Faculty of Science University of Copenhagen
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collected by the ITk will be a major challenge due to the extremely high combinatorics involved in the high-luminosity conditions of the HL-LHC. Without significant improvements in reconstruction algorithms
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for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high-dimensional data. Develop modular