264 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "St" "St" Fellowship positions in Portugal
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assessed according to the following weights and criteria: - Criterion 1: Absolute merit of curriculum vitae - Criterion 2: Academic performance in the areas of Machine Learning, Data and Information Fusion
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quality, consistency, and impact Contest Procedure Applications must be exclusively submitted on the admissions platform of the Instituto Superior Técnico at https://fenix.tecnico.ulisboa.pt/fenixedu
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, approved by Law No. 40/2004 of August 18, as amended by Decree-Law No. 65/2024 of October 1, and the University of Algarve Research Grant Regulations (https://files.dre.pt/2s/2021/10/210000000/0013700149.pdf
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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 Bachelor Positions Application
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 1 month ago
networks or similar machine learning technologies applied to DNA; Preferential: Experience with transcription factor motif discovery; Proficiency in high-throughput sequence alignment methods; Candidates who
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Procedure Applications must be exclusively submitted on the admissions platform of the Instituto Superior Técnico at https://fenix.tecnico.ulisboa.pt/fenixedu-admissions and requires registration and
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27 Feb 2026 Job Information Organisation/Company Instituto de Telecomunicações Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Bachelor
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13 Feb 2026 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions Application
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Computer Science (or close field) with strong foundations in data management, machine learning, and software engineering. Coursework or projects in NLP/LLMs, information retrieval, knowledge graphs/ontologies, data
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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 promotes cooperation