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the European Union through the COMPETE 2030 Programme, of Portugal 2030, under the following conditions: Scientific Area: Machine Learning Admission requirements: Candidates who cumulatively meet the following two
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Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0247.pdf CALL FOR GRANT APPLICATIONS (AE2026-0247) INESC TEC is now accepting grant applications to award 1 Research Grant (BI) within
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programme Reference Number AE2026-0222 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0222
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requirements: Candidates must hold, at the time of application, a Bachelor’s degree in Informatics Engineering or related fields. Candidates must also have knowledge in: i. Deep Learning and LLMs: practical
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programme Reference Number AE2026-0226 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0226
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programme Reference Number AE2026-0212 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0212
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Reference Number AE2026-0230 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0230.pdf CALL FOR
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Reference Number AE2026-0237 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0237.pdf CALL FOR
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candidates using photometry, spectral energy distributions and, when available, spectroscopic data. Both fellows will produce diagnostic plots and summary tables. Simple statistical or machine-learning methods
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planning and identification of strings and modules in the field. Development of a computer vision and machine learning pipeline for the detection, localisation and classification of defects in photovoltaic