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the attribution of (1) research grant within the scope of LASI - Intelligent Systems Associate Laboratory, reference LA/P/0104/2020, financed by national funds under the Multi‑Year Funding Program for R&D Units
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? Not funded by a EU programme Reference Number AE2026-0206 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt
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- One Method Does Not Fit All: Co-design of Context-aware Adaptive Mobile Authentication for Older Adults”, “2024.14974.PEX”, “DOI: https://doi.org/10.54499/2024.14974.PEX ”, funded by the Fundação para a
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of one (1) research grant within the scope of LASI - Intelligent Systems Associate Laboratory, reference LA/P/0104/2020, financed by national funds under the Multi‑Year Funding Program for R&D Units funded
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curricular evaluation purposes, proven skills in programming, preferably Python; machine learning and artificial intelligence; language models and retrieval-augmented generation (RAG); ASR/TTS; diarisation
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Intelligence (AI) algorithms, including Machine Learning (ML) and Deep Learning (DL) techniques, for advanced signal analysis. The work will focus on developing methodologies for the detection, extraction
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for this competition. Candidate admissibility requirements: Mandatory requirements: Have a Master’s degree in Bioinformatics, Informatics Engineering, Artificial Intelligence, Chemical and Biological Engineering
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the field of architecture or related fields; Proficiency in computer-aided design, graphics and video software, as well as data processing and word processing software, amongst others; Advanced knowledge
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the attribution of one (1) research grant within the scope of LASI - Intelligent Systems Associate Laboratory, reference LA/P/0104/2020, financed by national funds under the Multi‑Year Funding Program for R&D Units