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context.; Identification of data sources in lab conditions.; Identification of challenges and opportunities for machine learning approaches to improve the process.; Surveying the state of the art for
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scenarios., Experience with observability tools, particularly OpenTelemetry., Solid knowledge and experience in machine learning, deep learning, and large-language models (i.e., ResNet18, ResNet50, AlexNet
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domain in the design of deep learning algorithms for cardiovascular disease detection. 4. REQUIRED PROFILE: Admission requirements: Master’s degree in Biomedical Engineering, Computer Engineering
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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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.; - 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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PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning for lung cancer imaging data; - identify and select the appropriate methods for the study in question; - develop
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Requirements Academic qualifications: -. Minimum profile: Experience in Computer Vision and machine learning. Preference factors: Experience in research projects, and writing of scientific papers. Research
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21 Nov 2025 Job Information Organisation/Company INESC TEC Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile First Stage Researcher (R1
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PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning for lung cancer imaging data; - identify and select the appropriate methods for the study in question; - develop
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workload’s data (e.g., Deep Learning, Large Language Models) while addressing the I/O interference and fairness challenges faced by current distributed infrastructures, where storage resources are being shared