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Postdoctoral Fellowship at POSTECH Center for Mathematical Machine Learning and its Applications (CM2LA) The Center for Mathematical Machine Learning and its Applications (CM2LA), affiliated with the
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statistical mechanics, information theory, stochastic processes, population dynamics, and neural networks. Within this framework, machine learning systems and artificial generative models will also be
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Explainable AI (XAI) to ensure the transparency and verifiability of intelligent systems. These methodologies may be integrated with techniques such as machine learning, deep learning, data mining, and
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INFORMATICA - SCIENZA E INGEGNERIA | Bologna, Emilia-Romagna | Italy | about 1 month ago
Infrastructure? No Offer Description The research activity aims to investigate machine learning (ML) techniques supporting the design, synthesis, and analysis of collective and multi-scale systems, in
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georeferenced data acquired by mobile road monitoring systems using heterogeneous sensors, such as images, laser profilometers, GPS, and audio data, will integrate machine learning, computer vision, and image
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Theory, Optimal Transport Theory, Topology, Machine Learning Theory, High-dimensional Computational Geometry, Statistical Learning Theory and Statistical Inference. (2) Computing Theory for AI: Programming
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Consiglio Nazionale delle Ricerche-Istituto di Calcolo e Reti ad Alte Prestazioni | Napoli, Campania | Italy | 27 days ago
, and Data Mining techniques; Data preprocessing, feature selection, classification, and clustering; Programming languages and libraries for developing machine learning and deep learning applications
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA CIVILE, CHIMICA, AMBIENTALE E DEI MATERIALI | Bologna, Emilia-Romagna | Italy | 7 days ago
following storm surges. Specifically, the aim is to develop a machine learning model (such as neural networks, decision trees, random forests, or hybrid approaches) capable of analyzing multi-source
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execution of complex tasks. The research activities will include the development and integration of robot control algorithms, RGB-D vision systems, force sensing and machine-learning methods for robotic
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reference to hyperspectral imaging (HSI), X-ray fluorescence (XRF) and (micro)FTIR spectroscopy. Acquired data will be processed using statistical and chemometric methods, machine learning and artificial