57 machine-learning "https:" "https:" "https:" "https:" "The Open University" Undergraduate scholarships in Portugal
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programme (Norte2030) Where to apply Website https://domus.ipp.pt/documentos_publicos/index.html Requirements Research FieldEngineering » Computer engineeringEducation LevelUndergraduate LevelExcellent
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study cycle or non-award courses of Higher Education Institutions. Preference factors: Programming experience in Python; Knowledge of machine learning and computer vision Minimum requirements
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 12 days ago
engineering Researcher Profile First Stage Researcher (R1) Positions Undergraduate Positions Country Portugal Application Deadline 8 Jan 2026 - 23:59 (Europe/Lisbon) Type of Contract Not Applicable Job Status
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: d) Basic computer literacy from a user’s perspective. e) Strong verbal communication skills and fluency in English. f) Professional rigor and strong ability to work in a team. g) driving licence h
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the field of Artificial Intelligence and experience using machine learning and deep learning development environments and libraries is a plus. As set forth FCT Research Scholarship Regulation No. 950/2019
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, and amended by Decree-Law no. 123/2019 of 28 August, in its current wording (https://www.fct.pt/apoios/bolsas/estatutobolseiro ), and the FCT, I.P. Research Grants Regulation currently in force (https
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stipend amounts to 1040,98€ according to the table of values of the grants awarded directly by FCT, I.P. in the Country (https://www.fct.pt/apoios/bolsas/valores ). The payment will be made by bank
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: Scientific Area of Systems, Urbanism, Transportation and Environment Scholarship Theme: Performance tests of bituminous mixtures Objectives Learn how to use performance tests on bituminous mixtures and how
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Conditions: Knowledge in 3D modeling, additive manufacturing, computer vision. Good communication skills and fluency in oral and written Portuguese and English. Work Plan: Collaboration on various tasks within
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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