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fluorescence microscopy (SMLM, SIM), integrating physical-mathematical models, machine learning, and compressed sensing for accurate and efficient reconstructions. Applicants must submit a project implementing
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The goal of the research program is to develop machine learning techniques
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The goal of the research program is to develop machine learning techniques
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The research activity will focus on the development of algorithms for machine
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of signal processing and machine learning algorithms for the extraction of acoustic, prosodic, and semantic parameters from voice recordings. Alongside the innovative research activities, the project requires
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traditional and machine-learning and AI-based approaches will be used. Where to apply Website https://aunicalogin.polimi.it/aunicalogin/getservizio.xml?id_servizio=1079 Requirements Additional Information
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useful during underwater monitoring and exploration missions. Split computing provides a concrete means to enable the execution of high-performance machine learning models on sensory data collected by
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. The project aims to integrate machine learning, artificial intelligence (AI), and statistical modeling to analyze spatial transcriptomic data at a sub-cellular resolution, with the goal of advancing biomedical
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of renewable energy sources, with a focus on wind and photovoltaic plants. Through the integration of meteorological observations, high-resolution numerical models and machine learning algorithms, highly
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based on the new data generated, incorporating key variables identified in (i), and use statistical and machine learning methodologies to ensure high predictive accuracy and robustness; iii) validation