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) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Development of novel Machine Learning techniques applied in systems/networks research, which includes, but is not
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Machine Learning components of the CONVERGE project toolset.; - Assist in executing integration tests across different hardware and software modules.; - Contribute to the structured collection and
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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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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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learning models for generating artificial data using generative models. The result will be high-fidelity medical data. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - extend the knowledge
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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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models to characterize lung cancer based on a non-invasive methodology. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - extend the knowledge of the state of the art in machine learning
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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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-AI learning - Develop methodologies to assess the robustness and safety of human decisions assisted by AI, hybrid co-learning between AI and humans, and fully autonomous AI, considering risk assessment
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INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
systems; - experience in applying Artificial Intelligence/Machine Learning and/or optimization algorithms to wireless networking systems.; Minimum requirements: The four Research Initiation Grants to be