74 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" scholarships in Portugal
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
with setting up a streamflow forecasting system in Portugal and the advancement of scientific knowledge in machine learning probabilistic hydrological forecasting and decision-making optimized to act on
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|2025/795 under the scope of the Project Machine Unlearning in Speech Foundation Models: Learning to Forget (LeaF), Refª 2024.14611.CMU , funded Fundação para a Ciência e a Tecnologia, I.P., is now
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Escola Superior de Design, Gestão e Tecnologias da Produção de Aveiro - Norte da Universidade de Aveiro | Portugal | 14 days ago
Regulations of the University of Aveiro. 5. Work Plan: This project aims to develop solutions based on Artificial Intelligence for optimizing additive manufacturing processes. Machine learning techniques will
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by the European Research Council - ERC COG 101088763. The work for this position is in the area of Machine Learning, Decision Theory, Reinforcement Learning. Scientific Area: Information and Data
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of civil protection assets; - Researching and developing possible ways of calculating the risk of exposure of civil protection assets; - Applying machine learning algorithms to assist in risk calculation
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programme Reference Number AE2025-0527 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0527
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to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0554.pdf CALL FOR GRANT APPLICATIONS (AE2025-0554) INESC
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an emphasis on the development of methodologies and techniques for Evolutionary Computation and Machine Learning. Work plan: Review of the state of the art in Machine Learning and Deep Reinforcement Learning
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for further studies in the field of scientific computing involving machine learning models for viscoelastic fluid flows. Legislation and regulations: Law Nº. 40/2004, of 18th August, in its current wording
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approaches for binarized network models, identifying their strengths, limitations, and applicability within privacy-focused machine learning frameworks. Special attention will be given to evaluating