68 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" scholarships in Portugal
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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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on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: Experience in musical audio machine learning frameworks, advanced knowledge in music theory, and
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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
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/10.54499/2023.11234.PEX , funded by national funds through FCT/MECI, under the following conditions: Scientific Area: Machine Learning applied in Applied to Fluid Dynamics Simulation Admission requirements
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programme Reference Number AE2025-0509 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0509
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tools, with particular focus on multi-threaded and distributed scenarios. Experience with observability tools, particularly OpenTelemetry. Solid knowledge and experience in machine learning, deep learning
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: ● Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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of the state of the art in machine learning for generation of artificial data; - identify and select the appropriate methods for the study in question; - develop the research capacity through the application
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, for the period from 2021 -2026. Reference: BI/UTAD/116/2025 Scientific area/research field: Engineering Researcher profile: First Stage Researcher (R1) Admission requirements: Degree in Computer Engineering
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. Project Title: Machine learning techniques for crosstalk mitigation and new passive optical network architecturesHost institution: Iscte-IUL, PortugalThe LUMIRing project aims to deploy a MCF test bed