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INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
of the selected methodologies and approaches; - critically assess the research process and evaluate the results obtained.; 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: The four Research Initiation
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of the grant holder through the application of the selected methodologies and approaches; - critically assess the research process and evaluate the results obtained.; 3. BRIEF PRESENTATION OF THE WORK PROGRAMME
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 7 days ago
Biomedical Sciences, Biomedical Engineering, Pharmaceutical Sciences, Biochemistry, Bioengineering, or related fields with a minimum grade of 17/20; - Candidate must be enrolled in a PhD program preferably in
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scientific publications.; - Write the final activity report ; ; 4. REQUIRED PROFILE: Admission requirements: Master in Electric and Computer Engineering, Computer Science or similar The awarding
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26 Nov 2025 Job Information Organisation/Company INESC TEC Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1) Country Portugal Application Deadline 12 Dec
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21 Nov 2025 Job Information Organisation/Company INESC TEC Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile First Stage Researcher (R1
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26 Nov 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions Country
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biomedical image and signal processing; Previous experience in computer vision; Minimum requirements: Degree in Computer Science, Informatics Engineering, Data Science, Bioengineering or Applied Mathematics
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by the European Commission under the Horizon Europe program for the period 2021-2027. 1. GRANT DESCRIPTION Type of grant: Research Grant (BI) General scientific area: ENGINEERING Scientific subarea
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PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning for lung cancer imaging data; - identify and select the appropriate methods for the study in question; - develop