83 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "FORTH" positions at Universidade de Coimbra in Portugal
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solving. 5.Admission requirements: Those set forth in art. 17 of LTFP: a. Portuguese Nationality, when not dispensed by the Constitution, international convention or special law; b. 18 years of age; c. Not
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on the score of their academic qualifications. VII.VIII -All provisional and final jury decisions must be justified, recorded in minutes, and published on https://apply.uc.pt/ . VII.IX -Jury Composition
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, and published on https://apply.uc.pt/ . VII.VII- Jury Composition: President: Jorge Fernando Brandão Pereira Effective Members: Ana Maria Antunes Dias and Joana Teixeira Albuquerque Gomes Alternate
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qualifications. VII.VIII - All provisional and final jury decisions must be justified, recorded in minutes, and published on https://apply.uc.pt/ . VII.IX - Jury Composition: President: Maria Manueloa Monteiro
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. VII.VIII - All provisional and final jury decisions must be justified, recorded in minutes, and published on https://apply.uc.pt/ . VII.IX - Jury Composition: President: Isabel da Silva Henriques Effective
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minutes, and published on https://apply.uc.pt/ . VII.IX -Jury Composition: President: Paulo Jorge Rodrigues Amado Mendes Effective Members: Luís Manuel Cortesão Godinho and Andreia Sofia Carvalho Pereira
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Engineering, University of Coimbra III- Scientific supervision/coordination of the grant: Mahmoud Tavakoli IV - Work Plan / Goals to be achieved: To study and develop methods for fabrication of multi-layer
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collaboration; Orientation towards change and innovation; Orientation towards results; Critical analysis and problem-solving. Where to apply Website https://www.apply.uc.pt/procedure/4vuvfknfnjyu7twr Requirements
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4 Mar 2026 Job Information Organisation/Company Universidade de Coimbra Department Department of Electrical and Computer Engineering Research Field Engineering » Electrical engineering Engineering
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: Academic performance in courses within the fields of Programming, Artificial Intelligence, Machine Learning, or related areas – 40%; VII.II- I – In the evaluation of the interview, candidates' performance