102 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" Fellowship scholarships in Portugal
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Electrical and Computer Engineering, and with a suitable scientific and professional curriculum may apply. The candidate(s) must be enrolled in a MSc program - art. 6º, n.4 b) https://diariodarepublica.pt/dr
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and Computer Engineering. INESC-ID’s research impact is focused on four Thematic Lines Energy transition Life and health technology Security and privacy. Societal digital transformation. INESC-ID
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submitted on the admissions platform of the Instituto Superior Técnico at https://fenix.tecnico.ulisboa.pt/fenixedu-admissions and requires registration and validation of the candidate's identity
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and Computer Engineering. INESC-ID’s research impact is focused on four Thematic Lines Energy transition Life and health technology Security and privacy. Societal digital transformation. INESC-ID
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Computer Engineering, and with a suitable scientific and professional curriculum may apply. The candidate(s) must be enrolled in a MSc program - art. 6º, n.4 b) https://diariodarepublica.pt/dr/detalhe
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background and relevant professional experience – 40% Evaluation of academic performance and/or relevant professional experience in machine learning, software engineering, or cybersecurity. Experience in
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analysis and bioinformatic analysis. Analysis of antimicrobial resistance phenotypes and genotypes. Applicable legislation and regulations: Statute of the Scientific Research Fellow: https://dre.pt/web/guest
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11 Mar 2026 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Application
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in mathematics and topics related to machine learning. EVALUATION CRITERIA The selection will be based on the following criteria: Academic CV (60%) Previous experience in related projects (20
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' performance will be assessed according to the following weights and criteria: - Criterion 1 - Knowledge in the areas of Bioinformatics, Artificial Intelligence and Machine Learning - Criterion 2 – Motivation