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; Distributed multi-agent sensing and cooperative positioning algorithms; Machine learning and data-driven methods for ambient awareness. Working Environment: The PhD will be conducted at the University
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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developed countries, smartphone penetration exceeds 80%. The automatic transport mode detection (TMD), when effectively exploited, possibly using some kind of machine learning algorithm, provides more
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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the
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multiple 2D images and multiple channels, (d) optimizing 2D projection viewpoints (dose reduction and time savings), (e) applying artificial intelligence and traditional machine learning models to noise
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, software and data engineering, data mining, machine learning, and Artificial Intelligence. Qualified candidates are invited to submit their applications through the web portal available at https
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-based transfer learning classification model for two-class motor imagery brain-computer interface. International Journal of Neural Systems (IJNS). https://doi.org/10.1142/S0129065719500254 * Kudithipudi
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states, charge density waves, superconductivity, and quantum magnetism - Kagome materials and superconducting hydrides - Machine learning interatomic potentials (MLIPs) and data-driven atomistic
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, please visit: https://qbm.genzentrum.lmu.de/application/ Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content