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experience – 40% Evaluation of academic performance and/or relevant professional experience in machine learning, AI, software engineering, or security-related domains. Research track record and scientific
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relevant areas (e.g., software engineering, cybersecurity, program analysis, machine learning), as evidenced by transcripts. Relevant professional or research experience in software security, static analysis
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(e.g., software engineering, cybersecurity, program analysis, machine learning). Relevant professional experience in software security, program analysis, or AI-driven code analysis. Scientific track
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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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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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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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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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the following conditions: OBJECTIVES | FUNCTIONS The purpose is to continue the research on Machine Learning methods applied to optimization techniques, in particular for the veicule routing problem. The idea is
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23 Dec 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Country Portugal