25 web-programmer-developer "https:" "https:" "https:" "UCL" "UCL" Fellowship positions at Universidade de Coimbra
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of Coimbra III- Scientific supervision/coordination of the grant: Bernardete Martins Ribeiro; PJorge Manuel Oliveira Henriques IV - Work Plan / Goals to be achieved: This project proposes the development
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Engineering, Faculty of Science and Technology, University of Coimbra III- Scientific supervision/coordination of the grant: Paulo Jorge Carvalho Menezes IV - Work Plan / Goals to be achieved: Development
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Application Deadline 30 Jan 2026 - 23:59 (Europe/Lisbon) Country Portugal Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? European Union / Next
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Foundation for Science and Technology (FCT), I.P., through the European Regional Development Fund (ERDF) through the Thematic Programme Innovation and Digital Transition (COMPETE 2030), under Portugal 2030
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languages: AMD Vivado, C, C++, Java, Phyton, Matalab/Simulink. Programmer-level knowledge of the Kernel in Linux Operating System and programming graphical interfaces in "Qt". CVs with proven knowledge in
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- Scientific supervision/coordination of the grant: Ricardo António Lopes Mendes, José Carlos Miranda Góis IV - Work Plan / Goals to be achieved: The objective of the IIMEX project is to develop a new family of
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of the candidate’s profile to the work plan to be developed (40%) VII.II- The evaluation of the criteria and the final classification will be based on a scale from 0 to 100, with scores rounded to the nearest
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record, the candidates' academic performance will be assessed according to the following weights and criteria: - Criterion 1: Adequacy of the candidate`s profile to the work plan to be developed
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and criteria: - Criterion 1: Academic merit – 40% - Criterion 2: Motivation and adequacy to the work plan to be developed – 60% VII.II- The evaluation of the criteria and the final classification will
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Plan / Goals to be achieved: The objective of this grant is to develop the fundamental steps for training and evaluating predictive models for code comprehension using multimodal data, namely EEG, HRV