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center, integrating it with low-latency gravitational-wave alert systems and Machine Learning (ML) pipelines. Omissis... Where to apply Website https://www.unibo.it/it Requirements Additional Information
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, designing, implementing, and evaluating ML models that address practical challenges across domains. The researcher will contribute to the development of a full machine learning pipeline, including data
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for testing machine learning algorithms applied to generative design in support of existing heritage regeneration processes. Where to apply E-mail reclutamento.docenti@ateneo.uniroma3.it Requirements Additional
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predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time
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of signal processing and machine learning algorithms for the extraction of acoustic, prosodic, and semantic parameters from voice recordings. Where to apply Website https://aunicalogin.polimi.it/aunicalogin
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objective is to achieve a more stable, adaptive, and generalizable PSOG system with fast calibration and robust performance under domain variations. Where to apply Website https://aunicalogin.polimi.it
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the dynamics of potentially illegal waste deposits. The research will apply deep learning and computer vision techniques to identify regions within an image where there is an increase or decrease in
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, we believe science can achieve its fullest potential. THE ROLE During your internship you will work on a projectin the Cultural Heritage Technologies (https://www.iit.it/it/web/cultural-heritage
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, we believe science can achieve its fullest potential. THE ROLE During your internship you will work on a projectin the Cultural Heritage Technologies (https://www.iit.it/it/web/cultural-heritage
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machine learning techniques for building efficient reduced-order models in the context of the numerical simulation of parameterized partial differential equations. The analysis of recent deep learning