99 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" uni jobs at Politecnico di Milano
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based on machine learning tools for energy problems related to prediction. The application domains include both industry and climate changes. The first two months will be devoted to the study of
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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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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
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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 candidate will be involved in the development and implementation of machine
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: “Towards a trustworthy strategic use of data in machine learning pipelines”. CUP: D53C25002380001. Where to apply Website https://aunicalogin.polimi.it/aunicalogin/getservizio.xml?id_servizio=1079
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strategic use of data in machine learning pipelines”. CUP: D53C25002380001. Where to apply Website https://aunicalogin.polimi.it/aunicalogin/getservizio.xml?id_servizio=1079 Requirements Additional
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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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modelled from an energy and environmental standpoint by analysing the performance of the individual processes and/or machines that are most relevant in terms of resource consumption (energy, water, etc
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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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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