57 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" Fellowship positions at INESC TEC
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Reference Number AE2025-0579 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0579.pdf CALL FOR
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: ● Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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of the state of the art in machine learning for generation of artificial data; - identify and select the appropriate methods for the study in question; - develop the research capacity through the application
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programme Reference Number AE2025-0547 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0547
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programme Reference Number AE2025-0548 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0548
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programme Reference Number AE2025-0530 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0530
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Programme? Not funded by a EU programme Reference Number AE2025-0575 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https
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Programme? Not funded by a EU programme Reference Number AE2025-0574 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https
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of programming and artificial intelligence.; - Knowledge of deep learning and computer vision.; - Autonomy. Minimum requirements: Strong knowledge of the English language (written and spoken). 5. EVALUATION
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programme Reference Number AE2025-0563 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0563