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Website https://www.inesctec.pt/en/opportunity/AE2025-0532 Requirements Specific Requirements Academic qualifications: Training in Electrical and Computer Engineering. Minimum profile: • Be enrolled in a
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programme Reference Number AE2025-0527 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0527
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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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programme Reference Number AE2025-0509 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0509
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tools, with particular focus on multi-threaded and distributed scenarios. Experience with observability tools, particularly OpenTelemetry. Solid knowledge and experience in machine learning, deep learning
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on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: Experience in musical audio machine learning frameworks, advanced knowledge in music theory, and
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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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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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.; - Develop skills in artificial intelligence and machine learning techniques for analyzing operational data and detecting anomalies, using foundational model approaches (e.g., GridFM project, LF Energy
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with a focus on traditional machine learning (shallow learning) and deep learning methodologies. Knowledge of Data Science, including the development of data analysis and visualisation pipelines. 5