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TEC. 2. OBJECTIVES: Collaborate with clinical partners in data collection and annotation Design and implement new deep learning solutions for the analysis of heart sound auscultation, electrocardiogram
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, energy consumption, and accuracy.; ; Training deep learning models, especially in LLMs, faces critical challenges that compromise the optimal use of GPUs. These bottlenecks result in poor computational
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 14 days ago
, financed by national funds through FCT/MCTES Workplan: To develop deep learning approaches for segmentation and classification of surgical videos. Duration: The research fellowships will have the duration
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limited to, deep reinforcement learning, federated learning, deep learning and meta learning. The overall aim is to improve the efficiency in cyber-physical systems, such as drone swarms, that support 5G
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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
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in several tasks within the project’s work plan, including: - Development of deep learning models (e.g., convolutional neural networks and vision transformers); - Presentation of results at consortium
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. This scholarship aims to support PhD-level studies on FAE by exploiting a new methodology that combines deep learning technology and knowledge graphs. The goal is to research and develop a new Decision Support
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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 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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-of-the-art deep neural networks for musical audio, with special focus on timbre analysis and manipulation.; - Identify and implement approaches for explainable ML models.; - Cooperate in writing scientific